DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 28 April 2026 have been fully considered but they are not persuasive. in particular, the applicant argues that Iwabuchi in view of Lakshman does not teach the claimed “obtaining a corresponding depth map for each texture image” as claimed, asserting that neither prior art fairly teaches the claimed limitations. However, it should be pointed out that Lakshman still relates to corresponding sets of single-view texture images and single-view depth images as presented in, ¶53-54 and fig. 1A, which describe the texture image and depth image both contain large numbers of pixels which relate to a field of view. Additionally, ¶89 presents that the texture images comprise all pixels in an image frame. When this teaching combines with the fact that the texture image and depth image are corresponding sets, it can be understood that there are corresponding depth values for each pixel in the image frame of the texture image. for this reason, although the applicant may disagree, Lakshman does still describe the claimed limitation of corresponding depth maps to pixels in a corresponding texture image.
The applicant then argues that Iwabuchi with Lakshman fails to teach obtaining a plurality of texture images by asserting that Lakshman does not teach obtaining a plurality of texture images and generating a focal plane image since the ¶43 of Lakshman relates to sampled views corresponding to a respective viewpoint to a 3D scene. However, it should be pointed out that each prior art was relied upon to teach different aspects of the claimed obtained corresponding depth map for each texture image and the generated focal plane images for each texture image. It still needs to be pointed out that Iwabuchi relates to the capture of images at a plurality of focused object distances D1 to D3 which contain the focused object portions Ob1 to Ob3 that are transformed from the images captured at the plural focus distances, see Iwabuchi ¶34 and fig. 2A. For this reason, Iwabuchi does teach the claimed obtained texture images at different focal distances. Additionally Iwabuchi relates to correction of the images based on a form of weighting, but not explicitly. Lakshman was relied upon to teach particularly this deficiency, which can be used to improve the correction of Iwabuchi by using the blending function of Lakshman. The prior art teaches weighting of the pixels of a texture image based on the depth values of the corresponding pixels, which is similar to what is claimed, see Lakshman ¶96-97. While both Iwabuchi in view of Lakshman individually do not expressly teach the claimed focal plane image generation of the claimed invention, the combination teaches the texture images with corresponding depth maps, and the generated focal plane images as claimed. for this reason, the examiner maintains the rejection.
Rejection of claims 15 and 19 are maintained for the same reasons as disclosed above. See the responses above which explain why Iwabuchi with Lakshman teach the limitations of claims 15 and 19.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-3,7-8,19-20,22,25-26 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1)
Regarding claim 1, Iwabuchi teaches,
A method (¶32 and Fig. 1, “image capturing operation” by imaging device depicted in fig. 1) comprising:
obtaining a plurality of texture images of a scene, (¶34,38, Fig. 2 and 3, “images are captured” at a plurality of focused object distances D1 to D3 “of an object portion which is focused (hereafter focused object portion) Ob1 to Ob3 from the captured image” when at step S2 repeatedly “captures an image” at set “focused object distance” as disclosed in Fig. 3) each texture image having a different respective focal distance; (¶34,38, Fig. 2 and 3, “images are captured” at a “plurality of focused object distances D1 to D3” as depicted in fig. 2) and
obtaining a corresponding depth map (¶34-35,39, and Fig. 2, extracted “object image data OD1 to OD3” corresponds to “detected focused object portion Ob1 to Ob3” corresponds to object distances “D1 to D3”, disclosed in fig. 2) for each texture image; (¶34-35 and Fig. 2, “captured image data P1 to P3” which correspond to “focused object portion Ob1 to Ob3”) and
for each texture image, (¶40 and Fig. 3, “image processing” to the “focused object image data” as disclosed in Fig. 3) generating a focal plane image (¶40,60-93, and Fig. 3, steps S6-S9 image processing performs “transform” at step S6, “brightness” correct at step S7, “color saturation” correct at step S8, and “gradation processing” at step S9 on the captured “focused object image data”) by (i) determining a corresponding focal weight (¶87-90, Fig. 3,10, and 13, “respective color saturation” corresponding to step S8 disclosed in Fig. 3 “according to focused object distances D91 to D95” disclosed in Fig. 10) for the texture image, (¶87-90, Fig. 3,10, and 13, “respective color saturation” for each “focused object image data OD91 to OD95” according to focused object distances as disclosed in Fig. 10) wherein the focal weight (¶87-90, Fig. 3,10, and 13, “respective color saturation” corresponding to step S8 disclosed in Fig. 3 and 10) represents an amount by which the pixel is in focus, (¶87-90, Fig. 10 and 13, “focused object distance and color saturation are corresponded” of the pixel values of captured “focused object image data”) (ii) processing the texture image by the corresponding focal weight. (¶87-89, Fig. 3,10, and 13, color saturation correction processing “corrects the respective color saturation of the focused object image data OD91 to OD95, so that the color saturation corresponds to the focused object distance” which corresponds to step S8 disclosed in Fig. 3)
But does not explicitly teach,
(i) determining a corresponding focal weight for each of a plurality of pixels of the texture image, and (ii) multiplying a pixel value of each of the plurality of pixels by the corresponding focal weight,
wherein each of the corresponding depth maps comprises an indication of depth for each pixel in the corresponding texture image.
However, Lakhsman teaches additionally,
generating a focal plane image (¶96-98, “blending operations” performed to composite a “composited image C”) by (i) determining a corresponding focal weight (¶96, “different weights for the different warped texture images may be set”) for each of a plurality of pixels (¶96, different weights may be set based on individual “individual pre-warped depth values of pre-warped pixels, individual warped depth values of the warped pixel after the pre-warped pixels are warped to the warped pixel”) of the texture image, (¶96, “different weights for the different warped texture images” based on the depth values) and (ii) multiplying a pixel value of each of the plurality of pixels (¶96-99, “different weights” assigned to different “image portions with different depths” in compositing operations that include performing “weighted averaging of warped texture pixel values at a given warped pixel (position) of an overall warped image”) by the corresponding focal weight, (¶96-97, “Closer neighboring sampled views may be assigned higher weights in blending operations, whereas more distant neighboring sampled views may be assigned lower weights in the blending operations”)
wherein each of the corresponding depth maps (¶53-54 and fig. 1A, “single-view depth image 108” corresponding to single-view texture image 106 depicted in fig. 1A) comprises an indication of depth for each pixel (¶53-54 and fig. 1A, single-view texture image 106 and the single-view depth image 108 with “large numbers of pixels (e.g., texture image pixels, depth image pixels, etc.)” that correspondingly cover the field of view) in the corresponding texture image. (¶53-54 and fig. 1A, “single-view texture image 106”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman which performs a weighted averaging of texture image pixels by assigning different weights according to depth. This allows for accounting of occlusion/disocclusion of pixels in the image.
Regarding claim 2, Iwabuchi with Lakshman teaches the limitations of claim 1,
Iwabuchi teaches additionally,
displaying the focal plane images (¶30,40, and Fig. 3, “transferred to a display device 16” that displays a three-dimensional image based on the “parallax image data” generated by procedure which uses the “focused object image data” with “color saturation correction processing” of step S8, disclosed in Fig. 3) at the respective focal distance (¶30,40,87-90, Fig. 3,10, and 13, “focused object image data”, used in generating “parallax image data”, with “color saturation correction processing” of step S8 performed to adjust the color saturation according to “the focused object distances”, disclosed in Fig. 3,10, and 13) thereof in a multi-focal-plane display. (¶30 and 40, “display device 16” displays a “three-dimensional image based on the parallax image data”)
Regarding claim 3, Iwabuchi with Lakshman teaches the limitations of claim 2,
Iwabuchi teaches additionally,
focal plane images are displayed (¶30,40, and Fig. 3, “transferred to a display device 16” that displays a three-dimensional image based on the “parallax image data” generated by procedure which uses the “focused object image data” with “color saturation correction processing” of step S8, disclosed in Fig. 3) substantially simultaneously. (¶30 and 37, displayed three-dimensional image based on “parallax image data” includes right eye image data of combined “object image data rOD1 to rOD3” and left eye image data synthesized from “focused object image data OD1 to OD3”)
Regarding claim 7, Iwabuchi with Lakshman teaches the limitations of claim 1,
Iwabuchi teaches additionally,
corresponding depth map (¶34-35,39, and Fig. 2, extracted “object data OD1 to OD3” corresponding to “detected focused object portion Ob1 to Ob3” corresponds to object distances “D1 to D3”, disclosed in fig. 2) for each texture image (¶34-35 and Fig. 2, “captured image data P1 to P3” which correspond to “focused object portion Ob1 to Ob3 from the captured image data”) is captured at the focal distance (¶34-35 and Fig. 2, corresponding to “focused object distance D1 to D3”) of the corresponding texture image. (¶34,38, Fig. 2 and 3, “images are captured” at a plurality of focused object distances D1 to D3 “of an object portion which is focused (hereafter focused object portion) Ob1 to Ob3 from the captured image” when at step S2 repeatedly “captures an image” at set “focused object distance” as disclosed in Fig. 3)
Regarding claim 8, Iwabuchi with Lakshman teaches the limitations of claim 1,
Iwabuchi teaches additionally,
obtaining the plurality of texture images (¶34 and Fig. 2, “images are captured”) comprises capturing each of the plurality of texture images (¶34 and Fig. 2, images are captured at a “plurality of focused object distances D1 to D3”) at the respective focal distance; (¶34 and Fig. 2, “focused object distances D1 to D3”) and
obtaining the corresponding depth map (¶35 and Fig. 2, focused “object image data OD1 to OD3” corresponds to “focused object image data”) comprises capturing each depth map of the scene (¶35 and Fig. 2, “object image data OD1 to OD3 corresponding to each focused object portion Ob1 to Ob3” are extracted) focused at the respective focal distance. (¶35 and Fig. 2, “focused object image data OD1 to OD3 and the focused object distance D1 to D3, as the distance information, are corresponded”)
Regarding claim 19, Iwabuchi teaches,
A method (Title, “3D imaging system”) comprising:
obtaining a plurality of texture images (¶34,38, Fig. 2 and 3, “images are captured” at a plurality of focused object distances D1 to D3 “of an object portion which is focused (hereafter focused object portion) Ob1 to Ob3 from the captured image” when at step S2 repeatedly “captures an image” at set “focused object distance” as disclosed in Fig. 3) and respective corresponding depth maps (¶34-35,39, and Fig. 2, extracted “object image data OD1 to OD3” corresponds to “detected focused object portion Ob1 to Ob3” corresponds to object distances “D1 to D3”, disclosed in fig. 2) of a scene, (¶34-35,29, and Fig. 2, “captured image data P1 to P3” which correspond to “focused object portion Ob1 to Ob3” of light from object Ob that “forms an object image”) each texture image having a different respective focal distance; (¶34,38, Fig. 2 and 3, “images are captured” at a “plurality of focused object distances D1 to D3” as depicted in fig. 2) and
for each texture image, (¶40 and Fig. 3, “image processing” to the “focused object image data” as disclosed in Fig. 3) generating a focal plane image (¶40,60-93, and Fig. 3, steps S6-S9 image processing performs “transform” at step S6, “brightness” correct at step S7, “color saturation” correct at step S8, and “gradation processing” at step S9 on the captured “focused object image data”) by processing the texture image by a respective weight value, (¶87-89, Fig. 3,10, and 13, color saturation correction processing “corrects the respective color saturation of the focused object image data OD91 to OD95, so that the color saturation corresponds to the focused object distance” which corresponds to step S8 disclosed in Fig. 3) the respective weight value (¶87-90, Fig. 3,10, and 13, “respective color saturation” corresponding to step S8 disclosed in Fig. 3 and 10) being determined based at least in part on a depth value (¶87-90, Fig. 3,10, and 13, “respective color saturation” corresponding to step S8 disclosed in Fig. 3 “according to focused object distances D91 to D95” disclosed in Fig. 10) corresponding to the respective depth map (¶87-90, Fig. 3,10, and 13, “respective color saturation” for each “focused object image data OD91 to OD95” according to focused object distances as disclosed in Fig. 10) corresponding to the texture image. (¶87-90, Fig. 10 and 13, “focused object distance and color saturation are corresponded” of the pixel values of captured “focused object image data”)
But does not explicitly teach,
generating a focal plane image by multiplying a pixel value of each of the plurality of pixels by a respective weight value, the respective weight value being determined based at least in part on a depth value corresponding to the pixel in the respective depth map corresponding to the texture image,
wherein each of the corresponding depth maps comprises an indication of depth for each pixel in the corresponding texture image.
However, Lakshman teaches additionally,
generating a focal plane image (¶96-98, “blending operations” performed to composite a “composited image C”) by multiplying a pixel value of each of the plurality of pixels (¶96-99, “different weights” assigned to different “image portions with different depths” in compositing operations that include performing “weighted averaging of warped texture pixel values at a given warped pixel (position) of an overall warped image”) by a respective weight value, (¶96-97, “Closer neighboring sampled views may be assigned higher weights in blending operations, whereas more distant neighboring sampled views may be assigned lower weights in the blending operations”) the respective weight value (¶96, “different weights for the different warped texture images may be set”) being determined based at least in part on a depth value corresponding to the pixel (¶96, “different weights for the different warped texture images” set based on individual “individual pre-warped depth values of pre-warped pixels, individual warped depth values of the warped pixel after the pre-warped pixels are warped to the warped pixel”) in the respective depth map corresponding to the texture image, (¶96, “different weights for the different warped texture images” based on the depth values)
wherein each of the corresponding depth maps (¶53-54 and fig. 1A, “single-view depth image 10” corresponding to single-view texture image 106 depicted in fig. 1A) comprises an indication of depth for each pixel (¶53-54 and fig. 1A, single-view texture image 106 and the single-view depth image 108 with “large numbers of pixels (e.g., texture image pixels, depth image pixels, etc.)” that correspondingly cover the field of view) in the corresponding texture image. (¶53-54 and fig. 1A, “single-view texture image 106”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman which performs a weighted averaging of texture image pixels by assigning different weights according to depth. This allows for accounting of occlusion/disocclusion of pixels in the image.
Regarding claim 20, dependent on claim 19, it is the method limitation similar to claim 2, dependent on claim 1. Refer to rejection of claim 2 to teach the rejection of claim 20.
Regarding claim 22, Iwabuchi in view of Lakshman teaches the limitation of claim 19,
Iwabuchi teaches additionally,
the respective weight value (¶87-90, Fig. 3,10, and 13, “respective color saturation” corresponding to step S8 disclosed in Fig. 3 and 10) represents an amount by which the pixel is in focus. (¶87-90, Fig. 10 and 13, “focused object distance and color saturation are corresponded” of the pixel values of captured “focused object image data”)
Regarding claim 25, Iwabuchi in view of Lakshman teaches the limitation of claim 1,
Lakshman teaches additionally,
plurality of texture images (¶96-100, “L1 texture image “L1_t”, L2 texture image “L2_t””) each represent a capture of the scene from a same viewpoint, (¶86,60-63, and fig. 1B, “L1 texture image “L1_t” of the target view is different from “L2 texture image “L2_t” as different image layers of the “sampled view” in the view direction (104) as depicted in fig. 1B) and
wherein the plurality of texture images (¶96-100, “L1 texture image “L1_t”, L2 texture image “L2_t””) each use a different respective focal distance. (¶96-100,76, and fig. 1B, “texture image” transformed into visual object depicted in the second view associated with different layers at “different distances” as depicted in fig. 1B)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman which performs a weighted averaging of texture image pixels by assigning different weights according to depth. This allows for accounting of occlusion/disocclusion of pixels in the image.
Regarding claim 26, Iwabuchi in view of Lakshman teaches the limitation of claim 1,
Lakshman teaches additionally,
corresponding depth maps (¶60-63 and fig. 1B, “depth image 108-1 (denoted as “L1 depth”)” and “depth image 108-2 (denoted as “L2 depth”)” depicted in fig. 1B) is different depending on the respective focal distance. (¶60-63,76, and fig. 1B, “depth image 108-1” and “depth image 108-2” associated with respective texture image L1 and L2 associated with different layers at “different distances” as depicted in fig. 1B)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman which performs a weighted averaging of texture image pixels by assigning different weights according to depth. This allows for accounting of occlusion/disocclusion of pixels in the image.
Claim(s) 6,9 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1) in view of ALREGIB; Ghassan et al. (US 20120120192 A1)
Regarding claim 6, Iwabuchi with Lakshman teaches the limitations of claim 1,
But does not explicitly teach the additional limitations of claim 6,
However, Alregib teaches additionally,
wherein for each texture image, (¶88-90 and fig. 10, preprocessing of the “wrapped color image”) the focal weight (¶88-90 and Fig. 10, “w[i, j] is the assigned weight at pixel location [i, j]”) of each pixel (¶88-90 and fig. 10, “pixel location [i, j]”) in the texture image (¶88-90 and fig. 10, pixel location [i, j] of the depth adaptive preprocessed “wrapped color image”) is determined based at least in part on a difference (¶88-90 and fig. 10, assigned weight “w[i, j]” according to “mapping function” as a function of disparity “D[i, j]” expressed in terms of a proportional function of “focal length F, camera base line B, and depth Z”) between the focal distance (¶88-90 and Fig. 10, “focal length F”) of the texture image that includes the pixel (¶88-90 and Fig. 10, disparity D[i, j] “at pixel location [i, j]” as a function of focal length F adaptively preprocessing “wrapped color image”) and a depth value (¶88-90 and Fig. 10, “depth Z” expressed in disparity function as “Z[i, j]”) of the pixel in the corresponding depth map. (¶88-90 and Fig. 10, disparity D[i, j] “at pixel location [i, j]” as a function of depth Z at location “Z[i, j]” when adaptively preprocessing “wrapped color image”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with the depth-based view synthesis of Alregib which assigns depth adaptive weights to particular pixel locations in a color image. This can help reduce blur by assigning higher weights to edges of an image feature that helps create a seamless and natural looking synthesized view.
Regarding claim 9, Iwabuchi with Lakshman teaches the limitations of claim 1,
But does not explicitly teach the additional limitations of claim 9,
However, Alregib teaches additionally,
focal weight wi(x,y) of a pixel (¶88-90 and fig. 10, assigned weight “w[i, j]” at “pixel location [i, j]”) in texture image i (¶88-90 and fig. 10, “wrapped color image” used to generate “depth-weighted color image” through depth adaptive preprocessing) is determined as a function of a depth zi(x,y) of the pixel, (¶88-90 and fig. 10, assigned weight w[i, j] at pixel location [i, j] determined based on disparity “D[i, j]” which further expresses depth Z “Z[i, j]” at pixel location “[i, j]”) such that wi(x,y) = wi[zi(x,y)]. (¶88-90 and fig. 10, assigned weight “w[i, j]” at “pixel location [i, j]” determined based on disparity “D[i, j]” which further expresses depth Z “Z[i, j]” at pixel location “[i, j]”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with the depth-based view synthesis of Alregib which assigns depth adaptive weights to particular pixel locations in a color image. This can help reduce blur by assigning higher weights to edges of an image feature that helps create a seamless and natural looking synthesized view.
Claim(s) 10 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1) in view of ALREGIB; Ghassan et al. (US 20120120192 A1) in view of YOKOKAWA; Masatoshi et al. (US 20200007760 A1)
Regarding claim 10, Iwabuchi in view of Lakshman with Alregib teaches the limitation of claim 9,
But does not teach the additional limitations of claim 9,
However, Yokokawa teaches additionally,
w[zi(x,y)] has a maximum value when zi(x,y) is substantially equal to the focal distance of the texture image i. (¶165 and Fig. 11, “ weight of the pixel value of the divided pixel image is raised at the focal point located in a region identical to a depth of the AF position or a region at a depth close to this depth” of the image “Pic1” as depicted in Fig. 11)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with the depth-based view synthesis of Alregib with the weighting of Yokokawa which is based on the focal point being located at a depth of the auto focus position. This provides for an appropriate blending position point determination onto the auto focusing position.
Claim(s) 15-16,23 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1) in view of YOKOKAWA; Masatoshi et al. (US 20200007760 A1)
Regarding claim 15, it is the system claim of method claim 1.
Iwabuchi teaches additionally,
A system (¶28 and Fig. 1, “imaging device” depicted in Fig. 1) comprising:
a processor; (¶28,31 and Fig. 1, imaging device to which “processor of this embodiment is applied” such as “processor 4 includes a microcomputer or ASIC” as depicted in Fig. 1)
cause the processor (¶31 and Fig. 1, processor 4 “systematically controls the operation of the imaging device 2” depicted in fig. 1) to:
but does not explicitly teach the non-transitory computer-readable medium of claim 15,
However, Yokokawa teaches additionally,
a non-transitory computer-readable medium (¶351, “recording medium”) storing instructions operative, (¶351, “a program constituting the software is installed from a recording medium”) when executed by the processor, (¶351, “general-purpose personal computer” capable of executing various functions under various programs installed into the computer “from a recording medium”) to cause the processor (¶351, general-purpose personal computer where “processes are executed by software”) to:
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with the executable software of Yokokawa which performs a series of processes from dedicated hardware. The processes of this image processing can take advantage of the hardware configuration of a personal computer.
Refer to rejection of claim 1 to disclose the additional limitations of claim 15.
Regarding claim 16, Iwabuchi with Lakshman with Yokokawa teaches the limitations of claim 15,
Iwabuchi teaches additionally,
for each texture image, (¶34-35 and Fig. 2, “captured image data P1 to P3” which correspond to “focused object portion Ob1 to Ob3 from the captured image data”) amount by which the texture image is in focus (¶34-35 and Fig. 2, “detects an object portion which is focused (hereafter focused object portion) Ob1 to Ob3 from the captured image data P1 to P3”) is determined based at least in part on a depth value (¶34-35 and Fig. 2, “object portion which is focused (hereafter focused object portion) Ob1 to Ob3” for each “focused object distance D1 to D3, as the distance information” corresponds with focused object portion Ob1 to Ob3)
Lakshman teaches additionally,
for each of the plurality of pixels of the texture image, (¶96, “warped texture pixel values at a given warped pixel (position)” from individual warped texture images”) amount by which the pixel in the texture image is in focus (¶96-100, different “weights for the different warped texture images” based on the “depth values” of the “pixels in their respective single-view images”) is determined based at least in part on a depth value corresponding to the pixel. (¶97, Different weights “assigned to different images with different linear and/or angular distances”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with the executable software of Yokokawa which performs a weighted averaging of texture image pixels by assigning different weights according to depth. This allows for accounting of occlusion/disocclusion of pixels in the image.
Regarding claim 23, Iwabuchi in view of Lakshman with Yokokawa teaches the limitation of claim 15,
Iwabuchi teaches additionally,
displaying the focal plane images (¶30,40, and Fig. 3, “transferred to a display device 16” that displays a three-dimensional image based on the “parallax image data” generated by procedure which uses the “focused object image data” with “color saturation correction processing” of step S8, disclosed in Fig. 3) at the respective focal distance (¶30,40,87-90, Fig. 3,10, and 13, “focused object image data”, used in generating “parallax image data”, with “color saturation correction processing” of step S8 performed to adjust the color saturation according to “the focused object distances”, disclosed in Fig. 3,10, and 13) thereof in a multi-focal-plane display.(¶30 and 40, “display device 16” displays a “three-dimensional image based on the parallax image data”)
Claim(s) 24 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1) in view of YOKOKAWA; Masatoshi et al. (US 20200007760 A1) in view of ALREGIB; Ghassan et al. (US 20120120192 A1)
Regarding claim 24, dependent on claim 15, it is the system claim of method claim 6, dependent on claim 1. Refer to rejection of claim 6 to teach rejection of claim 24.
Claim(s) 11 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1) in view of Sasaki; Takashi (US 20180259743 A1)
Regarding claim 11, Iwabuchi in view of Lakshman teaches the limitation of claim 1,
But does not explicitly disclose the additional limitation of claim 11,
However, Sasaki teaches additionally,
amount by which the pixel in the texture image is in focus (¶42, “302 calculates a defocus amount for each target pixel position” using the “A image and the B image”) is determined based at least in part on a defocus map generated from the texture image. (¶42, “defocus map generating unit (hereinafter, simply referred to as a “map generating unit” 302 calculates a defocus amount for each target pixel position” such that defocus amount is information related to “the distance distribution of the object, and represent the value of the defocus map data”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with the map generation of Sasaki which generates a defocus map. The defocus map can represent spatial distribution of defocused areas where low exposure occurred.
Claim(s) 12-13 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1) in view of Das; Sujata (US 20170127046 A1)
Regarding claim 12, Iwabuchi in view of Lakshman teaches the limitation of claim 1,
But does not explicitly disclose the additional limitation of claim 12,
However, Das teaches additionally,
Generating a virtual viewpoint by shifting (¶97, “pixels are shifted horizontally between left and right images”) at least one of the focal plane images by an amount inversely proportional to the display focal distance of the respective focal plane image. (¶63 and 97, “applying depth associated with the plane having the fit to the at least one area to shift pixels in the two-dimensional image” by “shifting inversely proportional to the depth of the pixel from the viewer”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with the depth correction of Das which shifts images based on the proportionality of the depth of the pixel from the viewer. This allows for producing a complete stereo image pair.
Regarding claim 13, Iwabuchi in view of Lakshman with Das teaches the limitation of claim 12,
Das teaches additionally,
displaying the generated virtual viewpoint as one of a stereo pair of viewpoints. (¶97, “apply the depth of the planes or masks to the areas in the image to produce a stereoscopic image, e.g., anaglyph, or stereoscopic image pair for display on visual output 120 by viewer 170”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with the depth correction of Das which shifts images based on the proportionality of the depth of the pixel from the viewer. This allows for producing a complete stereo image pair.
Claim(s) 14 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1) in view of Das; Sujata (US 20170127046 A1) in view of Kroon; Bart (US 20140118509 A1)
Regarding claim 14, Iwabuchi in view of Lakshman with Das teaches the limitation of claim 12,
But does not explicitly disclose the additional limitation of claim 14,
However, Kroon teaches additionally,
displaying the generated virtual viewpoint in response to viewer head motion to emulate motion parallax. (¶96 and 99, “user moves his head, the presented images follow this movement to provide a motion parallax effect and a natural 3D experience” such that rendering viewpoint “changes continuously to follow the viewer's head movements”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with the depth correction of Das with the display rendering viewpoint of Kroon which follows the movement of a user’s head. This allows for producing a natural user experience with a strong motion parallax effect.
Claim(s) 18 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1) in view of YOKOKAWA; Masatoshi et al. (US 20200007760 A1) in view of Das; Sujata (US 20170127046 A1)
Regarding claim 18, dependent on claim 15, it is the system claim of method claim 12, dependent on claim 1. Refer to rejection of claim 12 to teach rejection of claim 18.
Claim(s) 21 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1) in view of Akeley; Kurt et al. (US 20160307368 A1)
Regarding claim 21, Iwabuchi in view of Lakshman teaches the limitation of claim 19,
But does not explicitly disclose the additional limitation of claim 21,
However, Akeley teaches additionally,
the plurality of respective weight values associated with a respective texture image of the plurality of texture images add up to 1. (¶151, “weighted-color arithmetic may be used to combine the remapped colors, with weights chosen such that they sum to one, and are in inverse proportion to the distance of the hull-image RCoP from the view RCoP”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with the weight arithmetic of Akeley where weights are chosen so that they sum to one. This technique helps avoids large changes.
Claim(s) 27 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1) in view of Vondran, JR.; Gary Lee et al. (US 20150104074 A1)
Regarding claim 27, Iwabuchi in view of Lakshman teaches the limitation of claim 1,
But does not explicitly teach the additional limitation of claim 27,
However, Vondran teaches additionally,
corresponding depth maps comprises (¶69-70, captured “multiple images”) an indication of a sharp transition between content at different depths. (¶69-70, captured “multiple images” having different “focus points and/or different depths of field” then selectively “blending or combining sharp and blurred regions of the multiple images to simulate the effect of refocusing to a particular depth”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the blending of Lakshman with multiple images of Vondran which are images at different focal points. This allows for an arrangement which can calibrate focusing onto specific scenes.
Claim(s) 28-29 rejected under 35 U.S.C. 103 as being unpatentable over IWABUCHI; Hiroshi et al. (US 20110316981 A1) in view of Chen; Liang-Gee et al. (US 20080080852 A1) in view of LAKSHMAN; Haricharan et al. (US 20180359489 A1)
Regarding claim 28, Iwabuchi teaches,
A method (¶32 and Fig. 1, “image capturing operation” by imaging device depicted in fig. 1) comprising:
obtaining a plurality of texture images of a scene, (¶34,38, Fig. 2 and 3, “images are captured” at a plurality of focused object distances D1 to D3 “of an object portion which is focused (hereafter focused object portion) Ob1 to Ob3 from the captured image” when at step S2 repeatedly “captures an image” at set “focused object distance” as disclosed in Fig. 3) each texture image representing a view of a scene captured from a single viewpoint (¶29, imaging unit 7 with single lens unit 6 forming “object image” via “light from the object Ob” where the “focused object distance is changed”) using a different respective focal distance; (¶34,38, Fig. 2 and 3, “images are captured” at a “plurality of focused object distances D1 to D3” as depicted in fig. 2 such that an imaging unit 7 “captures images using focused object distances D1 to D3”)
obtaining a corresponding depth map (¶34-35,39, and Fig. 2, extracted “object image data OD1 to OD3” corresponds to “detected focused object portion Ob1 to Ob3” corresponds to object distances “D1 to D3”, disclosed in fig. 2) for each texture image of the plurality of texture images, (¶34-35 and Fig. 2, “captured image data P1 to P3” which correspond to “focused object portion Ob1 to Ob3”)
for each texture image, (¶40 and Fig. 3, “image processing” to the “focused object image data” as disclosed in Fig. 3) generating a focal plane image (¶40,60-93, and Fig. 3, steps S6-S9 image processing performs “transform” at step S6, “brightness” correct at step S7, “color saturation” correct at step S8, and “gradation processing” at step S9 on the captured “focused object image data”) by (i) determining a corresponding focal weight (¶87-90, Fig. 3,10, and 13, “respective color saturation” corresponding to step S8 disclosed in Fig. 3 “according to focused object distances D91 to D95” disclosed in Fig. 10) for the texture image, (¶87-90, Fig. 3,10, and 13, “respective color saturation” for each “focused object image data OD91 to OD95” according to focused object distances as disclosed in Fig. 10) wherein the focal weight (¶87-90, Fig. 3,10, and 13, “respective color saturation” corresponding to step S8 disclosed in Fig. 3 and 10) represents an amount by which the pixel is in focus, (¶87-90, Fig. 10 and 13, “focused object distance and color saturation are corresponded” of the pixel values of captured “focused object image data”) and (ii) processing the texture image by the corresponding focal weight, (¶87-89, Fig. 3,10, and 13, color saturation correction processing “corrects the respective color saturation of the focused object image data OD91 to OD95, so that the color saturation corresponds to the focused object distance” which corresponds to step S8 disclosed in Fig. 3)
But does not explicitly teach,
each of the corresponding depth maps comprising depth values representing the depth of the scene taken from the single viewpoint using the focal distance of the corresponding texture image; and
(i) determining a corresponding focal weight for each of a plurality of pixels of the texture image, the focal weights for the pixels in the texture image being determined based on the depth values of the corresponding depth map, and (ii) multiplying a pixel value of each of the plurality of pixels of the texture image by the corresponding focal weight,
wherein each of the corresponding depth maps comprises depth values indicating depth for each pixel in the corresponding texture image; and
visually reproducing the scene by displaying the focal plane images at the corresponding focal distances using a multi-focal plane display.
However, Chen teaches additionally,
each of the corresponding depth maps (¶49,45, Fig. 2 and 6, “background depth map”) comprising depth values representing the depth of the scene taken (¶45,49, Fig. 2 and 6, “each pixel of the plural multi-focus images 211 has a depth value” obtained by a “focus measure and depth estimation via the computation device 23”) from the single viewpoint using the focal distance of the corresponding texture image; (¶44-45,50, “plural multi-focus images 211”, taken by capturing device 22 with an auto focus module 221, where the “plural multi-focus images are taken at several different focal lengths in a specific period”) and
visually reproducing the scene by displaying the focal plane images (¶44, “produce a left image 214 for left eye of user and a right image 215 for right eye of user”) at the corresponding focal distances (¶44, “all-in-focus image 212”, based on “plural multi-focus images 211”, used to produce a left image 214 for left eye of user and a right image 215 for right eye of user) using a multi-focal plane display. (¶44 and 49, “produce a left image 214” and “a right image 215” thereby “displaying the stereo 3D image” such as “Anaglyph Glasses, LCD-Shutter Glasses, LCD with Micro-retarder, two-view auto-stereoscopic 3D-LCD, 9-views 3D-LCD, and Polarized DLP Projector”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the focus lens based stereo image generation of Chen which takes multi-focus images and generates depth values for those multi-focus images using a focus measure and depth estimation. The techniques of Chen can help obtain stereo 3D images simply and efficiently.
Lakshman teaches additionally,
generating a focal plane image (¶96-98, “blending operations” performed to composite a “composited image C”) by (i) determining a corresponding focal weight (¶96, “different weights for the different warped texture images may be set”) for each of a plurality of pixels (¶96, different weights may be set based on individual “individual pre-warped depth values of pre-warped pixels, individual warped depth values of the warped pixel after the pre-warped pixels are warped to the warped pixel”) of the texture image, (¶96, “different weights for the different warped texture images” based on the depth values) the focal weights for the pixels in the texture image (¶96, “different weights for the different warped texture images” set based on individual “individual pre-warped depth values of pre-warped pixels, individual warped depth values of the warped pixel after the pre-warped pixels are warped to the warped pixel”) being determined based on the depth values of the corresponding depth map, (¶96 and 29, different weights for the different individual warped texture images based on “pre-warped depth values of pre-warped pixels” for pairs of “texture images and depth maps for a set of sampled views”) and (ii) multiplying a pixel value of each of the plurality of pixels (¶96-99, “different weights” assigned to different “image portions with different depths” in compositing operations that include performing “weighted averaging of warped texture pixel values at a given warped pixel (position) of an overall warped image”) by the corresponding focal weight, (¶96-97, “Closer neighboring sampled views may be assigned higher weights in blending operations, whereas more distant neighboring sampled views may be assigned lower weights in the blending operations”)
wherein each of the corresponding depth maps (¶53-54 and fig. 1A, “single-view depth image 108” corresponding to single-view texture image 106 depicted in fig. 1A) comprises depth values indicating depth for each pixel (¶53-54 and fig. 1A, single-view texture image 106 and the single-view depth image 108 with “large numbers of pixels (e.g., texture image pixels, depth image pixels, etc.)” that correspondingly cover the field of view) in the corresponding texture image; (¶53-54 and fig. 1A, “single-view texture image 106”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the focus lens based stereo image generation of Chen with the blending of Lakshman which performs a weighted averaging of texture image pixels by assigning different weights according to depth. This allows for accounting of occlusion/disocclusion of pixels in the image.
Regarding claim 29, Iwabuchi teaches,
A method, (¶32 and Fig. 1, “image capturing operation” by imaging device depicted in fig. 1) performed by a display, (¶32 and Fig. 1, imaging device depicted in fig. 1 with “display device 16” that displays “a three-dimensional image”) comprising:
obtaining a plurality of texture images of a scene (¶34,38, Fig. 2 and 3, “images are captured” at a plurality of focused object distances D1 to D3 “of an object portion which is focused (hereafter focused object portion) Ob1 to Ob3 from the captured image” when at step S2 repeatedly “captures an image” at set “focused object distance” as disclosed in Fig. 3) from a same viewpoint, (¶29, imaging unit 7 with single lens unit 6 forming “object image” via “light from the object Ob” where the “focused object distance is changed”) each texture image having a different respective focal distance (¶29, imaging unit 7 with single lens unit 6 forming “object image” via “light from the object Ob” where the “focused object distance is changed”)
obtaining a corresponding depth map (¶34-35,39, and Fig. 2, extracted “object image data OD1 to OD3” corresponds to “detected focused object portion Ob1 to Ob3” corresponds to object distances “D1 to D3”, disclosed in fig. 2) for each texture image of the plurality of texture images, (¶34-35 and Fig. 2, “captured image data P1 to P3” which correspond to “focused object portion Ob1 to Ob3”)
for each texture image of the plurality of texture images, (¶38-40 and Fig. 3, “image processing” to the “focused object image data”, disclosed in Fig. 3, from captured image data with “object image data”) generating a focal plane image at the respective focal distance (¶40,60-93,35, and Fig. 2-3, steps S6-S9 image processing performs “transform” at step S6, “brightness” correct at step S7, “color saturation” correct at step S8, and “gradation processing” at step S9 on the captured “focused object image data” OD1 to OD3 corresponds to “focused object distance D1 to D3” as depicted in fig. 2) by (i) determining a corresponding focal weight (¶87-90, Fig. 3,10, and 13, “respective color saturation” corresponding to step S8 disclosed in Fig. 3 “according to focused object distances D91 to D95” disclosed in Fig. 10) for the texture image, (¶87-90, Fig. 3,10, and 13, “respective color saturation” for each “focused object image data OD91 to OD95” according to focused object distances as disclosed in Fig. 10) wherein the focal weight (¶87-90, Fig. 3,10, and 13, “respective color saturation” corresponds to step S8 disclosed in Fig. 3 and 10) represents an amount by which the pixel is in focus, (¶87-90, Fig. 10 and 13, “focused object distance and color saturation are corresponded” of the pixel values of captured “focused object image data”) and (ii) processing images by the corresponding focal weight, (¶87-89, Fig. 3,10, and 13, color saturation correction processing “corrects the respective color saturation of the focused object image data OD91 to OD95, so that the color saturation corresponds to the focused object distance” which corresponds to step S8 disclosed in Fig. 3)
But does not explicitly teach,
performed by a multi-focal plane display,
each texture image having a different respective focal distance along a single view from the same viewpoint,
wherein the plurality of texture images each represent a capture of the scene from the same viewpoint;
each corresponding depth map at the respective focal distance of the corresponding texture image;
(i) determining a corresponding focal weight for each of a plurality of pixels of the texture image, the focal weights for the pixels in the texture image being determined based on the corresponding depth map, and (ii) multiplying a pixel value of each of the plurality of pixels of the texture image by the corresponding focal weight,
wherein each of the corresponding depth maps at the respective focal distance of the texture image comprises an indication of depth for each pixel in the corresponding texture image; and
displaying the focal plane images at the respective focal distance thereof as a multi-focal plane representation in a multi-focal-plane display.
However, Chen teaches additionally,
performed by a multi-focal plane display, (¶44,49, and fig. 2, “3D display 24” connected to computation device 23as part of a system depicted in fig. 2 such as “Anaglyph Glasses, LCD-Shutter Glasses, LCD with Micro-retarder, two-view auto-stereoscopic 3D-LCD, 9-views 3D-LCD, and Polarized DLP Projector”)
each texture image (¶44,50, and fig. 2, “plural multi-focus 2D images 211” depicted in fig. 2) having a different respective focal distance (¶44 and 50, plural multi-focus images “taken at several different focal lengths”) along a single view from the same viewpoint, (¶44-45,50, and fig. 6, “plural multi-focus images 211”, taken by capturing device 22 with an auto focus module 221, where the “plural multi-focus images are taken at several different focal lengths in a specific period” which appear to be the same scene as depicted in fig. 6)
wherein the plurality of texture images each represent a capture of the scene from the same viewpoint; (¶50 and fig. 6, “plural multi-focus images are taken at several different focal lengths in a specific period”)
each corresponding depth map (¶49,45, Fig. 2 and 6, “depth value” of each “pixel of the plural multi-focus images 211”) at the respective focal distance of the corresponding texture image; (¶49,45, Fig. 2 and 6, depth value of each pixel of the plural multi-focus images 211 “taken at several different focal lengths in a specific period”)
displaying the focal plane images (¶44, “produce a left image 214 for left eye of user and a right image 215 for right eye of user”) at the respective focal distance (¶44, “all-in-focus image 212”, based on “plural multi-focus images 211”, used to produce a left image 214 for left eye of user and a right image 215 for right eye of user) thereof as a multi-focal plane representation in a multi-focal-plane display. (¶44 and 49, “produce a left image 214” and “a right image 215” thereby “displaying the stereo 3D image” such as “Anaglyph Glasses, LCD-Shutter Glasses, LCD with Micro-retarder, two-view auto-stereoscopic 3D-LCD, 9-views 3D-LCD, and Polarized DLP Projector”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the focus lens based stereo image generation of Chen which takes multi-focus images and generates depth values for those multi-focus images using a focus measure and depth estimation. The techniques of Chen can help obtain stereo 3D images simply and efficiently.
Lakshman teaches additionally,
generating a focal plane image (¶96-98, “blending operations” performed to composite a “composited image C”) by (i) determining a corresponding focal weight (¶96, “different weights for the different warped texture images may be set”) for each of a plurality of pixels (¶96, different weights may be set based on individual “individual pre-warped depth values of pre-warped pixels, individual warped depth values of the warped pixel after the pre-warped pixels are warped to the warped pixel”) of the texture image, (¶96, “different weights for the different warped texture images” based on the depth values) the focal weights for the pixels in the texture image (¶96, “different weights for the different warped texture images” set based on individual “individual pre-warped depth values of pre-warped pixels, individual warped depth values of the warped pixel after the pre-warped pixels are warped to the warped pixel”) being determined based on the corresponding depth map, (¶96 and 29, different weights for the different individual warped texture images based on “pre-warped depth values of pre-warped pixels” for pairs of “texture images and depth maps for a set of sampled views”) and (ii) multiplying a pixel value of each of the plurality of pixels (¶96-99, “different weights” assigned to different “image portions with different depths” in compositing operations that include performing “weighted averaging of warped texture pixel values at a given warped pixel (position) of an overall warped image”) of the texture image by the corresponding focal weight, (¶96-97, “Closer neighboring sampled views may be assigned higher weights in blending operations, whereas more distant neighboring sampled views may be assigned lower weights in the blending operations”)
wherein each of the corresponding depth maps at the respective focal distance of the texture image (¶52-54 and fig. 1A, “single-view depth image 108” corresponding to “single-view texture image 106” seen from the viewpoint of the sampled view as depicted in fig. 1A) comprises an indication of depth for each pixel (¶53-54 and fig. 1A, single-view texture image 106 and the single-view depth image 108 with “large numbers of pixels (e.g., texture image pixels, depth image pixels, etc.)” that correspondingly cover the field of view) in the corresponding texture image; (¶53-54 and fig. 1A, “single-view texture image 106”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the imaging device of Iwabuchi with the focus lens based stereo image generation of Chen with the blending of Lakshman which performs a weighted averaging of texture image pixels by assigning different weights according to depth. This allows for accounting of occlusion/disocclusion of pixels in the image.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/JOSEPH G USTARIS/Supervisory Patent Examiner, Art Unit 2483
/JIMMY S LEE/Examiner, Art Unit 2483
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