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 .
Claim Objections
Claim 16 is objected to because of the following informalities:
Line 2: the word “perfrom” should read “perform”.
Appropriate correction is required.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claims 1-3, 6, 9-11, 14, 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Han et al. (US 20150178933 A1, hereinafter “Han”) in view of Ogasawara (US 20200120322 A1, hereinafter “Ogasawara”).
Regarding claim 9,
Han teaches:
An image processing apparatus (Han: Fig. 9, Image frame conversion apparatus; ¶266, . . . exemplary units and algorithm steps in the embodiments described in this specification may be implemented by electronic hardware or a combination of computer software and electronic hardware . . . “),
comprising:
a memory storing a computer program and data generated by operation of the computer program (Han: ¶212-215, “. . . image frame conversion apparatus 900 includes. . . a memory . . . memory 930 is configured to store a file. The memory 930 may include a high-speed RAM memory, and may also include a non-volatile memory. . .”; Claim 19: “. . . a non-transitory processor-readable medium having processor-executable instructions stored . . .”);
and a processor coupled to the memory and configured to execute the computer program to perform (Han: ¶212-214, “. . . a processor . . . The processor 910 is configured to execute a program. . .”; NOTE: Also see Fig. 9 illustrating the processor coupled to the memory.):
obtaining a first image, the first image being a two-dimensional (2D) image (Han: ¶117, “Step S100: Extract a longest line segment of a 2D image frame”; NOTE: The first image, which is a 2D image is inherently obtained. In order to process the 2D image frame, it requires obtaining a 2D image first.);
processing the first image to obtain a first view and a second view, the first view corresponding to a first viewpoint, the second view corresponding to a second viewpoint, (Han: ¶145, “After the first depth image D.sub.h processed by cross bilateral filtering is obtained, a virtual left view and right view may be generated according to the first depth image D.sub.h and the original image frame by using a depth image based rendering technology”; NOTE: The first image is the original image. The first view corresponding to a first viewpoint is the left view, and the second view corresponding to a second viewpoint is the right view.),
wherein the first view and the second view are used to achieve three-dimensional (3D) image output (Han: ¶149, “For the generated virtual left view and right view, . . . channels are merged, and finally a 3D view . . . may be obtained. Therefore, a 2D image frame is converted into a 3D image frame, that is, a 2D image is converted into a 3D image”).
However Han fails to teach: an image quality of the first view being lower than an image quality of the second view.
The analogous art Ogasawara teaches:
an image quality of the first view being lower than an image quality of the second view (Ogasawara: Abstract, “. . .an image generating device (200) generates an image for the right eye (272) at a standard resolution and generates a display image for the left eye (270) at a lower resolution. . .”; NOTE: The left eye image has a lower resolution than the right eye image. An image having lower resolution is an image with lower quality.)
It would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to combine Han and Ogasawara and include: an image quality of the first view being lower than an image quality of the second view.
The reason for doing so “enables a reduction not only in the amount of data transmitted from the image generating device to the head mounted display but also in the amount of data transmitted from the head mounted display to the image generating device, allowing an increase in power consumption to be more appropriately prevented” (Ogasawara: ¶112).
Regarding claim 10, depending on 9,
The combination of Han and Ogasawara teaches:
The apparatus according to claim 9, wherein when processing the first image to obtain the first view and the second view, (NOTE: see rejection of claim 9),
Ogasawara further teaches:
the processor is further configured to perform:
at least according to a first resolution, processing the first image to obtain the first view corresponding to the first viewpoint (Ogasawara: ¶86, “. . . an image for the left eye, a display image 270 smaller in size than the image for the right eye is generated by reducing the resolution.”; ¶89, “In a case where the left eye dominant period changes back to the “right eye dominant,” . . . the resolution of the entire image may be uniformly reduced or the resolution may be reduced except for the area within the predetermined range from the gaze point as illustrated in FIG. 7. Note that the resolution of the surrounding area may be reduced”; NOTE: The first image is the image captured by an imaging unit as described in paragraph 51. Ogasawara generates a left eye image with reduced resolution, which correspond to the first view point. The first resolution is the reduced resolution of the portion (or entirety) of the undominant left eye image, ultimately generating a lower left eye image resolution compared to the right eye image.); and
according to a second resolution, processing the first image to obtain the second view corresponding to the second viewpoint (Ogasawara: ¶86, “. . . the image generating device 200 generates an image for the right eye 272 at a resolution corresponding to the display resolution. . .”; NOTE: The generated right eye image is the image corresponding to the second viewpoint. The resolution for the right eye image is generated according to the display resolution, which is the second resolution.);
wherein the first resolution is lower than the second resolution (NOTE: As described in paragraph 86, the resolution of the image for the left eye has a lower resolution than the image for the right eye.).
Regarding claim 11, depending on 10,
The combination of Han and Ogasawara teaches:
The apparatus according to claim 10,
wherein when processing the first image at least according to the first resolution to obtain the first view corresponding to the first viewpoint (NOTE: see rejection of claim 10),
the processor is further configured to perform:
Ogasawara further teaches:
processing the first image to obtain a first initial view corresponding to the first viewpoint (NOTE: As already discussed in the rejection of claim 10, Ogasawara’s system obtains images using an imaging unit as described in paragraph 51, then generates a left and right eye images. The left eye image is the obtained first initial view corresponding to the first viewpoint)
processing a first processing area in the first initial view according to the first resolution; and processing a second processing area in the first initial view according to the second resolution; (Ogasawara: ¶61-63, “FIG. 7 schematically illustrates an example . . . where the resolution is varied with the area. . . a gaze area 80b centered at a gaze point 76a is set to have the standard resolution, with an area outside the gaze area 80b set to have a lower resolution, as in an image 78. In the illustrated example, the gaze area 80b is shaped like a circle with a radius R1 . . .”; ¶89, “. . . the resolution may be reduced except for the area within the predetermined range from the gaze point as illustrated in FIG. 7. . .”; NOTE: The first initial view is one of the stereo image, and Fig. 7 shows one of the stereo image 78. Image 78 correspond to a first initial view. The first processing area in the first initial view is the area outside the circle gaze area and is processed according to a first resolution, which is set to have a lower resolution. The second processing area in the first initial view is the gaze area, the area within the circle and is processed according to the second resolution, which is set to standard resolution corresponding to the display resolution);
wherein the first processing area and the second processing area constitute the first view corresponding to the first viewpoint (NOTE: The area within the circle gaze area and the area outside the gaze area as shown in Fig. 7 constitutes the first view point).
Regarding claim 14, depending on 9,
The combination of Han and Ogasawara teaches:
The apparatus according to claim 9, wherein when processing the first image to obtain the first view and the second view (NOTE: As discussed in the rejection of claim 9, the combination of Han and Ogasawara generates left and right images from a 2D image to generate a 3D image),
Han further teaches:
the processor is further configured to perform:
obtaining an image parameter of the first image (Han: ¶92, “determine a motion vector of each pixel of the 2D video frame according to the video frame adjacent to the 2D video frame.”; NOTE: The parameter obtained is the motion vector of each pixel, the first image is the 2D video frame);
However, Han fails to teach: when the image parameter meets a processing condition, generating the first view corresponding to the first viewpoint according to a first generation method based on the first image, and generating the second view corresponding to the second viewpoint according to a second generation method based on the first image; and when the image parameter does not meet the processing condition, generating the first view corresponding to the first viewpoint and the second view corresponding to the second viewpoint according to the second generation method based on the first image; wherein an image quality corresponding to the first generation method is less than an image quality corresponding to the second generation method.
The analogous art Ogasawara teaches:
when the image parameter meets a processing condition, generating the first view corresponding to the first viewpoint according to a first generation method based on the first image, and generating the second view corresponding to the second viewpoint according to a second generation method based on the first image (Ogasawara: ¶38-40, “The motion detecting unit 52 uses at least either the captured images or the measured values from the motion sensor to determine whether or not the head is moving. . . When one of the values is larger than or equal to a threshold, the head is determined to be moving. When the values are smaller than the threshold, the head is determined to be stopped. . . Only one resolution reduction . . . the resolution may be varied in stages according to the speed range. . .”; ¶100, “In a case where the stop period transitions to the “motion period” when the head is determined to be moving, the image generating device reduces the resolution . . . a display image for the left eye . . . have the lower resolution”; NOTE: The parameter is the speed identified. If the speed value is higher than a threshold, then the system is in “motion period”, it then generates the undominant eye image, in this case the left image corresponding to a first viewpoint in a lower resolution, while the dominant eye right image has higher resolution. The first generation method is reducing the resolution of the left eye image such that it is less than the resolution of the right eye image if the system is determined to be in “motion period”));
and when the image parameter does not meet the processing condition, generating the first view corresponding to the first viewpoint and the second view corresponding to the second viewpoint according to the second generation method based on the first image (Ogasawara: ¶99, “. . . during the “stop period” . . . the image generating device generates display images 300 at the resolution corresponding to the display resolution. . .”; NOTE: if the speed value does not exceed the threshold, then it does not meet the processing condition to reduce the resolution of the left eye image, the system then generates the images to correspond the resolution of the display. The second generation method is generating the images with resolution to correspond the display resolution);
wherein an image quality corresponding to the first generation method is less than an image quality corresponding to the second generation method (NOTE: As discussed above, the first generation method is when the system is determined to be in “motion period” and reduce the resolution of the undominant eye image (left eye image) such that its resolution is less than the resolution of the dominant eye image. Because the undominant left eye image is reduced in quality by reducing its resolution (lower than the right eye image corresponding to the resolution of the display) in the first generation method (during motion period), and both images are generated to correspond the display resolution in the second generation method (during stop period, there is no reduction in resolution), therefore, an image quality corresponding to the first generation method is less than an image quality corresponding to the second generation method.
It would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to combine Han and Ogasawara and apply Ogasawara’s method using Han’s motion vector as input and include: when the image parameter does not meet the processing condition, generating the first view corresponding to the first viewpoint and the second view corresponding to the second viewpoint according to the second generation method based on the first image; wherein an image quality corresponding to the first generation method is less than an image quality corresponding to the second generation method.
The reason for doing so “an increase in the amount of data to be transmitted can be prevented with little adverse effect on perception of images, and power consumption can be reduced” (Ogasawara: ¶101).
Regarding claims 17-19 respectively,
Claims 17-19 respectively are drawn to an electronic device having the same computer program claimed in the apparatus of claims 9-11 respectively. Accordingly, the apparatus of claims 9-11 is an electronic device as described in Han paragraph 266. Therefore, claims 17-19 are drawn to electronic device having the same computer program claimed in the apparatus of claims 9-11 respectively and are rejected for the same reasons of obviousness as used above.
Regarding claims 1-3, and 6 respectively,
Claims 1-3, and 6 are drawn to the method corresponding to the computer program of using same as claimed in the apparatus of claims 9-11, and 14 respectively. Therefore, claims 1-3, and 6 are drawn to the method corresponding to the computer program of using same as claimed in the apparatus of claims 9-11, and 14 respectively and are rejected for the same reasons of obviousness as used above.
Claims 4, 5, 12-13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Han in view of Ogasawara further in view of Ban (US 20160286198 A1, hereinafter “Ban”).
Regarding claim 12, depending on 9,
The combination of Han and Ogasawara teaches:
The apparatus according to claim 9, wherein when processing the first image to obtain the first view and the second view (NOTE: see rejection of claim 9 regarding the left and right view)
the processor is further configured to perform:
processing the first image to obtain a first initial view corresponding to the first viewpoint, and filling the first initial view with content according to a first filling method to obtain the first view (Han: ¶147, “In the left view and right view obtained by projecting and mapping, because of depth discontinuity at edges, holes often appear at the edges of the generated virtual left view and right view, that is, pixels without information. In a possible implementation manner, background pixels may be used to fill those holes. . .”“NOTE: See rejection of claim 9, the first initial view corresponding to the first viewpoint is the left view image, the second initial view corresponding to the second viewpoint is the right view image, the first filling method is the using the background pixels to fill the holes.);
and processing the first image to obtain a second initial view corresponding to the second viewpoint (NOTE: See rejection of claim 9, the first initial view corresponding to the first viewpoint is the left view image, the second initial view corresponding to the second viewpoint is the right view image);
Although Han paragraph 147 teaches that “because of depth discontinuity at edges, holes often appear at the edges of the generated virtual left view and right view, that is, pixels without information. In a possible implementation manner, background pixels may be used to fill those holes”; and although Ogasawara teaches processing both left and right images where the image in the undominant eye (left or right) has lower resolution that saves power consumption due to less image processing on the image of the undominant eye,
the combination of Han and Ogasawara fails to teach: filling the second initial view with content according to a second filling method to obtain the second view;
Ban teaches:
converting a two-dimensional (2D) image into a three-dimensional (3D) image (Ban: ¶3) implementing an inpainting scheme to fill the corresponding hole regions with the textures of the reference image corresponding to the hole regions of the respective frames for left and right eye images (Ban: ¶48-51, “. . . image including all of holes included in the respective frames of the left-eye image and the right-eye image. . . fills hole regions of the reference image with textures corresponding to the hole regions of the reference image . . . fills the remaining hole regions in an inpainting scheme. . .”).
It would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to combine Han, Ogasawara, and Ban and include: filling the second initial view (NOTE: right eye image) with content (NOTE: texture corresponding to the hole regions of the reference image) according to a second filling method (NOTE: inpainting scheme) to obtain the second view (NOTE: The hole-filled right image).
The reason for doing so is “to provide an apparatus and a method for transforming image capable of rendering a three-dimensional (3D) image in which flickering for hole regions is not generated” (Ban: ¶12); and to further improve the quality of the image of the dominant right eye image using Ban’s inpainting scheme.
However still the above combination still fails to teach: wherein a content filling amount corresponding to the first filling method is less than a content filling amount corresponding to the second filling method.
It would have been obvious an obvious to try/design choice to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention among finite number of solutions:
(NOTE: first filling method = Han’s pixel filling, second filling method = Ban’s texture filling. Han’s pixel filling uses less resources as Ban’s texture comprise of multiple pixel.)
Left image (lower resolution)
Right image (higher resolution)
Content filling Amount
L (left); R (Right)
Solution 1-3
Pixel Filling
Pixel Filling
L = L; L > R; L < R
Solution 4-6
Pixel Filling
Texture Filling
L = L; L > R; L < R
Solution 7-9
Texture Filling
Pixel Filling
L = L; L > R; L < R
Solution 10-12
Texture Filling
Texture Filling
L = L; L > R; L < R
And try solution 6, and apply a first filling method (Han’s pixel filling) to the first initial view (Left eye image with lower resolution) and apply a second filling method (Ban’s texture filling) to the second initial view (Right eye image with higher resolution), wherein a content filling amount corresponding to the first filling method is less than a content filling amount corresponding to the second filling method.
The reason for doing so is to further improve quality of the image that is viewed by the dominant eye by using Ban’s texture filling, while keeping the image viewed by the undominant eye to be at reduced resolution having less amount of data to be processed. Additionally, in spite of having reduced resolution in the undominant eye, “simultaneously viewing the images allows three-dimensional shapes to be perceived as usual due to reconstruction in the brain. The present inventor's experiments indicate that the stereoscopic vision is prevented from being affected even in a case where the resolution of one of the stereo images is approximately one-fourths of the resolution of the other. Accordingly, the amount of data to be transmitted can be reduced with little adverse effect on the stereoscopic vision, allowing an increase in power consumption to be prevented (Ogasawara: ¶87).
Regarding claim 13, depending on 12,
The combination of Han, Ogasawara, and Ban teaches:
The apparatus according to claim 12,
Han further teaches:
wherein when filling the first initial view with content according to the first filling method to obtain the first view, the processor is further configured to perform:
according to the first filling method, filling a first filling area in the first initial view with content using pixels of a background area in the first image (Han: ¶147-148, “In the left view and right view obtained by projecting and mapping, because of depth discontinuity at edges, holes often appear at the edges of the generated virtual left view and right view, that is, pixels without information. In a possible implementation manner, background pixels may be used to fill those holes, as shown in a formula (6)”; ¶148, “where, s(x, y) indicates a pixel value of the coordinate position (x, y) in the image, w indicates a size of a window for filling a hole, values of u and v fall within a range of [-w, w], and non_hole(x, y) is used to mark whether a pixel in the coordinate position (x, y) in the image is a hole, where a value 0 indicates that the pixel in the position is a hole, and a value 1 indicates that the pixel in the position is not a hole, and that only a non-hole pixel in the window w is used to fill a hole”; NOTE: Also see formula 6. As described in Han paragraph 147-148, formula 6 is applied to for pixel filling for holes in the left image where it has a window size ‘w’. if the window only covers ‘background’ of the image, such that no foreground image is within the window, the formula will only use the ‘background pixels’. The first filling area is the area where only the background is within the window ‘w’”);
and according to the first filling method, filling a second filling area in the first initial view with content using pixels of a foreground area and the background area in the first image to obtain the first view (NOTE: Accordingly, if the window includes a foreground object, the formula inherently uses pixel information of the background and foreground areas. The second filling area will be the area captured by the window including portion of the background and foreground.);
wherein the first filling area and the second filling area constitute an area to be filled in the first initial view (NOTE: Since the first filling area (window capturing only background), and the second filling area (window capturing both a portion of background and foreground) are in the same left image during processing the left image, therefore they constitute an area to be filled in the first initial view).
Regarding claim 20,
Claim 20 is drawn to an electronic device having the same computer program claimed in the apparatus of claim 12. Accordingly, the apparatus of claims 12 is an electronic device as described in Han paragraph 266. Therefore, claim 20 is drawn to an electronic device having the same computer program claimed in the apparatus of claim 12 and is rejected for the same reasons of obviousness as used above.
Regarding claims 4-5 respectively,
Claims 4-5 respectively are drawn to the method corresponding to the computer program of using same as claimed in the apparatus of claims 12-13 respectively. Therefore, claims 4-5 are drawn to the method corresponding to the computer program of using same as claimed in the apparatus of claims 12-13 respectively and are rejected for the same reasons of obviousness as used above.
Claims 16, and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Han in view of Ogasawara further in view of Lopez et al. (US 20170085863 A1, hereinafter “Lopez”).
Regarding claim 16, depending on 9,
The combination of Han and Ogasawara teaches:
The apparatus according to claim 9, wherein when processing the first image to obtain the first view and the second view.
Although the combination of Han and Ogasawara teaches converting 2D image to 3D image by generating a left view image as the first viewpoint (undominant eye) and a right view image (dominant eye) as the second viewpoint, wherein the image for the left eye’s resolution is reduced such that its image quality is lower than the image for the right eye’s resolution, the combination of Han and Ogasawara does not use any machine learning model in their system, and therefore the combination of Han and Ogasawara does not teach:
the processor is further configured to perform: processing the first image using a first image generation model to obtain the first view corresponding to the first viewpoint; and processing the first image using a second image generation model to obtain the second view corresponding to the second viewpoint; wherein: the first image generation model is trained based on first input samples and first output samples, the first input samples are 2D image samples, and the first output samples are first view samples corresponding to the first viewpoint; the second image generation model is trained based on second input samples and second output samples, the second input samples are 2D image samples, and the second output samples are second view samples corresponding to the second viewpoint; and an image quality of the first view samples is lower than an image quality of the second view samples.
The analogous art Lopez teaches “Machine learning method that learns to convert 2D video to 3D video from a set of training examples” (Lopez: Abstract).
Lopez further teaches:
The processor is further configured to perform:
processing the first image using a first image generation model to obtain the first view corresponding to the first viewpoint; and processing the first image using a second image generation model to obtain the second view corresponding to the second viewpoint (Lopez: Claim 1, “. . . machine learning method of converting 2D video to 3D video, comprising: obtaining a training set comprising a plurality of conversion examples, each conversion example comprising a 2D scene . . . generating a stereoscopic image pair for each of said one or more object frames based on said object depth model, said stereoscopic image pair comprising a left image and a right image”; ¶100, “. . . machine learning system 1900 may include neural networks, deep learning systems, support vector machines, regression models, classifiers, decision trees, ensembles, genetic algorithms, hidden Markov models, and probabilistic models . . .”; ¶108, “. . . Embodiments may use machine learning for any portion or portions of the 2D to 3D conversion process . . .”; NOTE: Also see figure 22. The first image generation model is the machine learning model configured dedicated to obtain the left image, which is the first view corresponding to the first viewpoint. Similarly, the second image generation model is the machine learning model configured dedicated to obtain the right image, which is the second view corresponding to the second viewpoint);
wherein: the first image generation model is trained based on first input samples and first output samples, the first input samples are 2D image samples, and the first output samples are first view samples corresponding to the first viewpoint (Lopez: ¶94, “. . . Outputs of each step are fed back into the machine learning system for possible checking, correction, refinement, and adaptive tuning of the conversion algorithms . . .”; ¶99, “. . . a machine learning system . . . training the system on conversion examples. . .. A conversion example may include a 2D input 2203. . .” NOTE: 2D left image first input sample (is being fed back from the first generation model) >> first generation model dedicated to obtain left image >> outputs the left image corresponding to the first viewpoint to be fed back);
the second image generation model is trained based on second input samples and second output samples, the second input samples are 2D image samples, and the second output samples are second view samples corresponding to the second viewpoint (Lopez: ¶94, 99 as referenced above; NOTE: 2D left image second input sample (is being fed back from the first generation model) >> second generation model dedicated to obtain right image >> outputs the left image corresponding to the first viewpoint to be fed back);
It would have been an obvious design choice between applying machine learning / not apply machine learning for 2D to 3D image conversion to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to combine Han, Ogasawara, and Lopez, implementing machine learning method that learns to convert 2D video to 3D video from a set of training examples and include: the processor is further configured to perform: processing the first image using a first image generation model to obtain the first view corresponding to the first viewpoint; and processing the first image using a second image generation model to obtain the second view corresponding to the second viewpoint; wherein: the first image generation model is trained based on first input samples and first output samples, the first input samples are 2D image samples, and the first output samples are first view samples corresponding to the first viewpoint; the second image generation model is trained based on second input samples and second output samples, the second input samples are 2D image samples, and the second output samples are second view samples corresponding to the second viewpoint.
It would also have been obvious that the combination of Han, Ogasawara, and Lopez yields predictable result such that: an image quality of the first view samples is lower than an image quality of the second view samples because Ogasawara’s method reduces the left image’s resolution that is lower than the resolution of the right eye image. Lower quality, lower resolution. Therefore, the first view samples (reduced resolution left image) that goes into the first generation model have lower quality than the second view samples (higher resolution right image) that goes in the second generation model.
The reason for doing so is to “automate or semi-automate the conversion process” (Lopez: Abstract), “dramatically reduce the time and cost of 2D to 3D conversion” (Lopez: ¶94), “to track complexity, costs, budgets, status, capacity, and workload, and to forecast these variables for projects or tasks” (Lopez: ¶94).
Regarding claim 8,
Claims 8 is drawn to a method corresponding to the computer program of using same as claimed in the apparatus of claim 16. Therefore, claim 8 is drawn to a method corresponding to the computer program of using same as claimed in the apparatus of claim 16 and is rejected for the same reasons of obviousness as used above.
Claims 15, and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Han in view of Ogasawara further in view of Yamashita et al. (US 20100021141 A1, hereinafter “Yamashita”).
Regarding claim 15, depending on 9,
The combination of Han and Ogasawara teaches:
The apparatus according to claim 9,
However, the combination of Han and Ogasawara fails to teach: wherein: a first content in the first view is output to the first viewpoint through an output device, a second content in the first view is output to the second viewpoint through the output device, and the first content and the second content constitute the first view; and the second view is output to the second viewpoint through the output device.
The analogous art Yamashita teaches:
wherein: a first content in the first view is output to the first viewpoint through an output device (Yamashita: FIG. 10, NOTE: The first content in the first view (man/woman) in the first view is output to the first viewpoint (left-view output) through an output device (display device ¶380, Fig. 1)),
a second content in the first view is output to the second viewpoint through the output device (Yamashita: Fig. 10, NOTE: A second content in the first view (the sun in the left-view output image) is output to the second viewpoint (the sun is output to the right-view output, which is the second viewpoint ) through the output device (display device ¶380, Fig. 1)),
and the first content and the second content constitute the first view (Yamashita FIG 10: NOTE: The sun and the man/woman constitute the first view (left-view));
and the second view is output to the second viewpoint through the output device (Yamashita: Fig. 10, NOTE: the second view is the right-view output displayed through the output device (display device ¶380, Fig. 1)).
It would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to combine Han, Ogasawara, and Yamashita and include: wherein: a first content in the first view is output to the first viewpoint through an output device, a second content in the first view is output to the second viewpoint through the output device, and the first content and the second content constitute the first view; and the second view is output to the second viewpoint through the output device.
The reason for doing so is “to re-use the graphics for 2D playback, thus will be able to skip the conversion process of stereoscopic graphics (create a second view), resulting in a reduction of labor cost for generating stereoscopic contents” ensuring “the memory capacity of the playback apparatus will not be consumed even when an image obtained by compositing the video with the graphics is displayed stereoscopically” (Yamashita: ¶17-19), and to lessen the fatigue or stress caused to the eyes of the viewer (Yamashita: ¶227).
Regarding claim 7,
Claims 7 is drawn to a method corresponding to the computer program of using same as claimed in the apparatus of claim 15. Therefore, claim 7 is drawn to a method corresponding to the computer program of using same as claimed in the apparatus of claim 15 and is rejected for the same reasons of obviousness as used above.
Conclusion
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/PATRICK P GALERA/Examiner, Art Unit 2617 /KING Y POON/Supervisory Patent Examiner, Art Unit 2617
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