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 Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-6, 14-18 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Williams et al. (US 20130342690 A1).
Regarding claim 1. Williams discloses A video compression method ([0001] systems for improving quality of compressed video images), comprising:
acquiring a detection result of a first sensor, and determining a target motion parameter according to the detection result ([0008] the scene is illuminated by a sequence of light pulses with wavelengths outside the visible range, such as infrared. Light from the illuminated scene is sensed to provide a stream of images of the scene, which images are captured and processed for motion detection in the scene; [0033] motion vectors are derived from infrared images);
determining a video compression parameter according to the target motion parameter (figure 2, [0031] When video compression 18 detects motion during the compression process, to increase the frequency at which anchor frames are obtained (by increasing the frequency of image tagging), thereby increasing the proportion of anchor frames relative to non-anchor frames in the GOPs. For example, instead of only one I-frame in a group of nine frames as shown in GOP 30 in FIG. 2, one may wish to have one I-frame in each group of seven or five frames in the GOP. In certain embodiments, an arbitrary and changing number of extra I-frames may be captured in selected ones or all of the GOPs such as GOP 30 and 30' when it is important to capture moving objects or bodies in the scene (the size of a GOP corresponds to a video compression parameter)); and
performing video compression on first video data according to the video compression parameter (figure 1, [0036] The images from camera 14 from the scene are captured by video capture 16 and compressed by video compression 18; figure 2, [0031] When video compression 18 detects motion during the compression process, to increase the frequency at which anchor frames are obtained (by increasing the frequency of image tagging), thereby increasing the proportion of anchor frames relative to non-anchor frames in the GOPs. For example, instead of only one I-frame in a group of nine frames as shown in GOP 30 in FIG. 2, one may wish to have one I-frame in each group of seven or five frames in the GOP. In certain embodiments, an arbitrary and changing number of extra I-frames may be captured in selected ones or all of the GOPs such as GOP 30 and 30' when it is important to capture moving objects or bodies in the scene).
Regarding claim 2. Williams discloses The video compression method according to claim 1, wherein the first video data is video data captured by an image sensor (figure 1, [0013] Light from the scene is sensed by a camera 14, which provides images of the scene to an imaging capture device such as video capture block 16), and a detection region of the first sensor is overlapped with an image acquisition region of the image sensor ([0033] Camera 14 is preferably one that can sense both infrared light and human visible light, so that no extra camera is necessary. Alternatively, an additional camera may be deployed for recording images visible to humans).
Regarding claim 3. Williams discloses The video compression method according to claim 2, wherein the detection region of the first sensor being overlapped with the image acquisition region of the image sensor comprises: the detection region of the first sensor being larger than or equal to the image acquisition region of the image sensor ([0033] Camera 14 is preferably one that can sense both infrared light and human visible light, so that no extra camera is necessary. Alternatively, an additional camera may be deployed for recording images visible to humans).
Regarding claim 4. Williams discloses The video compression method according to claim 1, wherein the first sensor comprises any one or more of a radar sensor, an infrared sensor, and a laser sensor ([0008] the scene is illuminated by a sequence of light pulses with wavelengths outside the visible range, such as infrared. Light from the illuminated scene is sensed to provide a stream of images of the scene, which images are captured and processed for motion detection in the scene; [0033] motion vectors are derived from infrared images).
Regarding claim 5. Williams discloses The video compression method according to claim 1, wherein the target motion parameter comprises at least one of:
a quantity of moving targets, sizes of the moving targets and speeds of the moving targets ([0033] motion vectors are derived from infrared images).
Regarding claim 6. Williams discloses The video compression method according to claim 5, wherein the video compression parameter is an inter-frame gap (figure 2, [0031] When video compression 18 detects motion during the compression process, to increase the frequency at which anchor frames are obtained (by increasing the frequency of image tagging), thereby increasing the proportion of anchor frames relative to non-anchor frames in the GOPs. For example, instead of only one I-frame in a group of nine frames as shown in GOP 30 in FIG. 2, one may wish to have one I-frame in each group of seven or five frames in the GOP. In certain embodiments, an arbitrary and changing number of extra I-frames may be captured in selected ones or all of the GOPs such as GOP 30 and 30' when it is important to capture moving objects or bodies in the scene).
Regarding claim 14, the same analysis has been stated in claim 1.
Regarding claim 15, the same analysis has been stated in claim 1.
Regarding claim 16, the same analysis has been stated in claim 1.
Regarding claim 17, the same analysis has been stated in claim 5.
Regarding claim 18, the same analysis has been stated in claim 6.
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.
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.
Claims 7-8, 12-13, 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Williams et al. (US 20130342690 A1) in view of GROIS et al. (US 20200413051 A1) and Brailean et al. (US 5717463 A).
Regarding claim 7. GROIS discloses when the target motion parameter comprises the quantity of the moving targets and the speeds of the moving targets, the determining the video compression parameter according to the target motion parameter comprises:
determining the inter-frame gap according to an amount of motion (abstract, Based on the spatial complexity and the temporal complexity of the media content, a Group of Picture (GOP) size for the one or more frames of the media content may be determined. The GOP size may be inversely proportional to the spatial complexity and the temporal complexity of the one or more frames of media content; [0002] Determining the temporal complexity of the one or more frames of the media content may comprise determining an amount of motion between the one or more frames of the media content; [0018] The temporal complexity module 106 may analyze the differences between the frames in order to determine the amount of motion in the one or more frames of the media content. Such temporal complexity may be determined, for example, by means of the Mean Co-Located Pixel Difference (MCPD) metric, which indicates the difference between co-located pixels in consecutive frames. Variances between the frames may be calculated and evaluated. The larger the difference between the frames, the larger the motion complexity, which may lead to smaller GOP sizes; [0040] The GOP size for the one or more frames of the media content may be determined based on analyzing the spatial complexity associated with the one or more frames of the media content and/or the temporal complexity associated with the one or more frames of the media content (an amount of motion directly relates to the quantity and speed of motion within the video)).
Brailean discloses a method and system for estimating the motion within a video sequence provides very accurate estimates of both the displacement vector field, as well as, the boundaries of moving objects (abstract), wherein the quantity of the moving targets and the speeds of the moving targets are estimated (column 5 lines 33-35, an accurate segmentation of the current intensity frame (210) into regions or objects; column 5 lines 12-15, The output of the motion boundary estimator (106) is the first moving object boundary estimate (118), l.sub.k, and represents only the boundaries of objects that are moving within the video sequence; column 12 lines 39-40, the displacement of each pixel contained within a particular object is characterized; column 12 lines 57-60, The translational motion estimator determines the translational motion component for each object. This is accomplished by averaging the horizontal and vertical displacement components over each object).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the inventions of Williams, GROIS and Brailean, to represent the amount of motion by the quantity of the moving targets and the speeds of the moving targets, and to determine the inter-frame gap according to the quantity of the moving targets and the speeds of the moving targets, in order to decrease the bitrate without decreasing or substantially decreasing the overall quality of the video (GROIS abstract).
Regarding claim 8. Williams in view of GROIS discloses The video compression method according to claim 7, wherein the determining the inter-frame gap according to the quantity of the moving targets and the speeds of the moving targets comprises:
determining that the inter-frame gap is a first gap e1 if the quantity of the moving targets is greater than a first quantity threshold c1 or a speed of at least one of the moving targets is greater than a first speed threshold d1;
determining that the inter-frame gap is a second gap e2 if: the quantity of the moving targets is between the first quantity threshold c1 and a second quantity threshold c2, the speed of at least one of the moving targets is between the first speed threshold d1 and a second speed threshold d2, and speeds of other moving targets are not greater than the first speed threshold d1;
determining that the inter-frame gap is a third gap e3 if: the quantity of the moving targets is between the first quantity threshold c1 and the second quantity threshold c2 and the speeds of all of the moving targets are less than the second speed threshold d2; or the quantity of the moving targets is less than the second quantity threshold c2 and the speeds of all of the moving targets are between the first speed threshold d1 and the second speed threshold d2;
determining that the inter-frame gap is a fourth gap e4 if the quantity of the moving targets is less than the second quantity threshold c2 and greater than 0, and the speeds of all of the moving targets are less than the second speed threshold d2; or
determining that the inter-frame gap is a fifth gap e5 if the quantity of the moving targets is 0 (Williams [0031] For example, … only one I-frame in a group of nine frames as shown in GOP 30 in FIG. 2; GROIS [0018] When it is determined that there is not much motion in the video content, the GOP size can be larger, thereby resulting in better coding efficiency by decreasing an overall amount of I or P frames);
wherein c1>c2>0, d1>d2>0 and 0<e1≤e2<e3<e4<e5.
The same motivation has been stated in claim 7.
Regarding claim 12. GROIS discloses when the target motion parameter comprises the sizes of the moving targets and the speeds of the moving targets, the determining the video compression parameter according to the target motion parameter comprises:
determining the inter-frame gap according to an amount of motion (abstract, Based on the spatial complexity and the temporal complexity of the media content, a Group of Picture (GOP) size for the one or more frames of the media content may be determined. The GOP size may be inversely proportional to the spatial complexity and the temporal complexity of the one or more frames of media content; [0002] Determining the temporal complexity of the one or more frames of the media content may comprise determining an amount of motion between the one or more frames of the media content; [0018] The temporal complexity module 106 may analyze the differences between the frames in order to determine the amount of motion in the one or more frames of the media content. Such temporal complexity may be determined, for example, by means of the Mean Co-Located Pixel Difference (MCPD) metric, which indicates the difference between co-located pixels in consecutive frames. Variances between the frames may be calculated and evaluated. The larger the difference between the frames, the larger the motion complexity, which may lead to smaller GOP sizes; [0040] The GOP size for the one or more frames of the media content may be determined based on analyzing the spatial complexity associated with the one or more frames of the media content and/or the temporal complexity associated with the one or more frames of the media content (an amount of motion directly relates to the size and speed of motion within the video)).
Brailean discloses a method and system for estimating the motion within a video sequence provides very accurate estimates of both the displacement vector field, as well as, the boundaries of moving objects (abstract), wherein the sizes of the moving targets and the speeds of the moving targets (column 5 lines 33-35, an accurate segmentation of the current intensity frame (210) into regions or objects; column 5 lines 12-15, The output of the motion boundary estimator (106) is the first moving object boundary estimate (118), l.sub.k, and represents only the boundaries of objects that are moving within the video sequence; column 6 lines 55-56, the size of an object, i.e. the number of pixels contained in an object; column 12 lines 39-40, the displacement of each pixel contained within a particular object is characterized; column 12 lines 57-60, The translational motion estimator determines the translational motion component for each object. This is accomplished by averaging the horizontal and vertical displacement components over each object).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the inventions of Williams, GROIS and Brailean, to represent the amount of motion by the sizes of the moving targets and the speeds of the moving targets, and to determine the inter-frame gap according to the sizes of the moving targets and the speeds of the moving targets, in order to decrease the bitrate without decreasing or substantially decreasing the overall quality of the video (GROIS abstract).
Regarding claim 13. Williams in view of GROIS discloses The video compression method according to claim 12, wherein the determining the inter-frame gap according to the sizes of the moving targets and the speeds of the moving targets comprises:
determining that the inter-frame gap is a first gap e1 if a size of at least one of the moving targets is greater than a first size threshold f1 or a speed of at least one of the moving targets is greater than a first speed threshold d1;
determining that the inter-frame gap is a second gap e2 if: the sizes of all of the moving targets are between the first size threshold f1 and a second size threshold f2, the speed of at least one of the moving targets is between the first speed threshold d1 and a second speed threshold d2, and speeds of other moving targets are not greater than the first speed threshold d1;
determining that the inter-frame gap is a third gap e3 if: the sizes of all of the moving targets are between the first size threshold f1 and the second size threshold f2, and the speeds of all of the moving targets are less than the second speed threshold d2; or the sizes of all of the moving targets are less than the second size threshold f2 and the speeds of all of the moving targets are between the first speed threshold d1 and the second speed threshold d2;
determining that the inter-frame gap is a fourth gap e4 if the sizes of all of the moving targets are less than the second size threshold f2, and the speeds of all of the moving targets are less than the second speed threshold d2; or
determining that the inter-frame gap is a fifth gap e5 if the quantity of the moving targets is 0 (Williams [0031] For example, … only one I-frame in a group of nine frames as shown in GOP 30 in FIG. 2; GROIS [0018] When it is determined that there is not much motion in the video content, the GOP size can be larger, thereby resulting in better coding efficiency by decreasing an overall amount of I or P frames);
wherein f1>f2>0, d1>d2>0 and 0<e1≤e2<e3<e4<e5.
The same motivation has been stated in claim 12.
Regarding claim 19, the same analysis has been stated in claim 7.
Regarding claim 20, the same analysis has been stated in claim 12.
Allowable Subject Matter
Claims 9-11 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/XIAOLAN XU/Primary Examiner, Art Unit 2488