DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . It is responsive to the submission dated 12/18/2023. Claims 1-15 are presented for examination.
Information Disclosure Statement
2. The information disclosure statements (IDSs) submitted on 01/08/2024 are in compliance with the provisions of 37 CFR 1.97 and are being considered by the Examiner.
Claim Rejections - 35 USC § 102
3. 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
4. Claims 1-5 are rejected under 35 U.S.C. 102(a1) as being anticipated by Wang (US 20170171445).
Considering claim 1, Wang discloses an apparatus (see figs. 2 and 4), comprising: a video camera (item 4, fig. 2) to capture an image of a participant on a video call (see paras. 4-5 and 34); an ambient light sensor (5, fig. 2) to detect light (see paras. 18-19); and a processor (item 200, fig. 4) communicatively coupled to the video camera and the ambient light sensor (see paras. 8 and 36), wherein the processor is to: identify a portion of a video image of the video call that includes the image of the participant (see paras. 4 and 34, wherein in applying the brightness adjustment of a person self-photographing during a video call, at least a portion of a video image of the video call that includes the person must be identified); detect a type of light on the participant based on the light detected by the ambient light sensor (see paras. 8-10 and 19); and
perform a light compensation to match a color range of the image of the participant and a color range of a background image selected for the video call based on the type of light that is detected (see paras. 4 and 31-34).
As per claim 2, Wang discloses a light source (see item 01, fig. 3) communicatively coupled to the processor (see paras. 8 and 36).
As per claim 3, Wang discloses the light compensation performed by the processor comprises adjusting a light intensity of the light source (See paras. 21-27).
As per claim 4, Wang discloses the ambient light sensor is to detect a direction of the light and a color of the light (see paras. 8 and 36).
As per claim 5, Wang discloses the processor to perform the light compensation further comprises a processor to: compare a color histogram of the image of the participant to a color histogram of the background image that is selected to determine an amount of the light compensation that is to be performed (See paras. 27 and 31-34).
6. Claims 6, 9-13 and 15 are rejected under 35 U.S.C. 102(a1) as being anticipated by Cao et al. (CN 110647865 A).
Considering claim 6, Cao discloses a method, comprising: detecting, by a processor, different types of light on an image of a participant of a video call (e.g. Cao teaches: the sample face image under various illumination scenes may include: indoor sample human face image, outdoor sample human face image, strong light sample human face image, weak light sample human face image, reverse light sample human face image, side light sample human face image and infrared sample human face image. see para. 142….The inverse light sample human face image can be the sample human face image shot by the camera when the shot human face is located between the camera and the light source. The average grey value of the irradiated human face in the human face image of the backlight sample is less than the average grey value of other areas except the irradiated human face in the backlight sample. The light source can be indoor light or outdoor sunshine. The camera can be common camera or infrared camera. The infrared sample face image can be the image shot by the infrared camera. The wavelength range corresponding to the human face image of the infrared sample can be the wavelength range of the infrared ray, for example, it can be 760 nm (nm) to 1 mm (mm). The wavelength range corresponding to the indoor sample human face image, the outdoor sample human face image, the strong light sample human face image, the weak light sample human face image, the reverse light sample human face image and the side light sample human face image can be the wavelength range of the visible light, such as 400 nm to 700 nm. See paras. 147-148);
dividing, by the processor, a frame of the video call into different regions
associated with the different types of light (e.g., In one example, the human face image is an ith frame of video frame, the ith frame of video frame is calibrated with a human face positioning frame, the human face positioning frame is obtained by identifying the (i-1) th frame of video frame by the human face frame positioning model 106, the image in the human face positioning frame is intercepted as an area image, inputting the region image of the ith frame video frame from the input layer 103, performing feature extraction on the region image through the common feature extraction model 101, obtaining an image feature vector, inputting the image feature vector into the illumination condition identification model 107, obtaining the illumination condition vector, The image feature vector and the illumination condition vector are simultaneously input to the attitude angle recognition model 102, the face recognition model 104, the five sense key point extraction model 105 and the face frame positioning model 107 for recognition. See para. 131. Various illumination scene images are illustrated in the above. Optionally, it may also be: the gray value of most pixels in the strong light sample face image (such as 70 % to 100 % of pixels) is greater than the gray value threshold value, the gray value of most pixels in the weak light sample face image (such as 70 % to 100 % of pixels) is less than or equal to the gray value threshold value, The gray value of most of the pixels (e.g., 70 % to 100 % of the pixels) in the first region in the side light sample face image is greater than the gray value threshold, and the gray value of most of the pixels (e.g., 70 % to 100 % of the pixels) in the second region is less than or equal to the gray value threshold. See para. 150);
applying, by the processor, different amounts of light compensation on different portions of a virtual background of the video call associated with the different regions of the frame of the video call based on a respective type of light that is detected (see paras. 142-147, and 150 and para. 218 for light compensation on different portions of a virtual background of the video call based on the different amounts of lights detected per image regions described in paras. 142-150); and
generating, by the processor, an updated image based on the different amounts
of light compensation that are applied (e.g., the gyroscope sensor 1712 can cooperate
with the acceleration sensor 1711 to collect the 3D action of the user to the computer device 1700…. And to perform image stabilization at the time of shooting… see para. See para. 223. In one embodiment, the processor 1701 may control the display brightness of the touch display screen 1705 based on the ambient light intensity collected by the optical sensor 1714. Specifically, when the ambient light intensity is high, the display brightness of the touch display screen 1705 is increased; When the ambient light intensity is low, the display brightness of the touch display screen 1705 is reduced. In another embodiment, the processor 1701 may also dynamically adjust the photographing parameters of the camera assembly 1706 based on the ambient light intensity collected by the optical sensor 1714. See para. 225).
As per claim 9, Cao discloses detecting, by the processor, a direction of each one of the different types of light sources; and dividing, by the processor, the frame of the video call into different regions based on the direction and a type of each one of the different types of light sources. See paras. 106 and 142-147.
As per claim 10, Cao discloses detecting, by the processor, a position of each one of the different types of light sources; and dividing, by the processor, the frame of the video call into different regions based on the position and a type of each one of the different types of light sources. See paras. 106 and 142-147.
Claim 11 contains features that correspond in scope with the limitations recited in claim 6. As the limitations of claim 6 were found anticipated by the teachings of Cao, it is readily apparent that the applied prior art performs the underlying elements. As such, the limitations of claim 11 are, therefore, subject to rejections under the same rationale as claim 6.
As per claim 12, Cao discloses detect a type of light source for each one of the number of light sources that is detected; and apply the light compensation to each one of the number of regions based on the difference in color and the type of light source. See paras. 218 and 225.
As per claim 13, Cao discloses adjusting a color of the second portion of the video frame within a region to match a color of the first portion of the video frame within the region or adjusting a color of the first portion of the video frame within a region to match a color of the second portion of the video frame within the region. See paras. 142-147 and 218.
As per claim 15, Cao discloses the processor to apply the light compensation comprises adjusting a color of the first portion of the video frame and a color of the second portion of the video frame within a region to match a target color range. See paras. 218 and 225-226.
Allowable Subject Matter
7. Claims 7-8, and 14 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, because the prior art of record fail to teach the method of claim 6, which further comprises: tracking, by the processor, a location of the image of the participant from a first frame to a second frame of the video call; changing, by the processor, the different portions of the virtual background associated with the different regions from the first frame to the second frame of the video call as the location of the image of the participant moves; and applying, by the processor, the light compensation to the different portions of the virtual background associated with the different regions in the second frame of the video call (as recited in claim 7); wherein the method of claim 6, further comprising repeating the detecting, the dividing, and the applying for a duration of the video call (as recited in claim 8). The prior art of record fails also to teach the non-transitory computer readable storage medium of claim 11, wherein the processor to apply the light compensation comprises identifying an obstruction for each one of the number of light sources, determining a shadow created on the first portion of the frame associated with the participant caused by the obstruction, and adjusting a color of the second portion of the video frame to include the shadow (as recited in claim 14).
Conclusion
8. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chen (US 20190356831) discloses a screen fill light photographing method and system for a mobile terminal includes detecting a first luminance information of a current environment, comparing the same with a luminance threshold, controlling, according to the comparison result, a powered-on or powered-off state of a screen fill light mode; and according to the state of the screen fill light mode, performing corresponding image processing of a photo.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to WESNER SAJOUS whose telephone number is (571)272-7791. The examiner can normally be reached on M-F 10:00 TO 7:30 (ET).
Examiner interviews are available via telephone and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice or email the Examiner directly at wesner.sajous@uspto.gov.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Said Broome can be reached on 571-272-2931. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/WESNER SAJOUS/Primary Examiner, Art Unit 2612
WS
08/08/2025
Prosecution Insights