DETAILED ACTION
This Office action for U.S. Patent Application No. 15/583,722 is responsive to communications filed 27 February 2027, in reply to the Non-Final Rejection of 5 December 2025 and the Interview of 13 February 2026.
Claims 1, 2, 5–14, 16–22, and 24–28 are pending, of which claims 25–28 are new.
In the previous Office action, claims 1–7, 18, 19, 22, and 24 were rejected under 35 U.S.C. § 103 as obvious over U.S. Patent Application Publication No. 2015/0222799 A1 (“Noorkami”) in view of U.S. Patent Application Publication No. 2017/0064148 A1 (“Muninder”). Claims 8, 10, 11, 14, 17, 20, and 21 were rejected under 35 U.S.C. § 103 as obvious over Noorkami in view of Muninder and in view of U.S. Patent Application Publication No. 2017/0034494 A1 (“Kang”). Claims 12, 13, 15, and 16 were found to contain material allowable over the prior art but were objected to as dependent on rejected base claims.
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, see pp. 10–14, filed 27 February 2026, with respect to the rejections of claims 1, 18, and 24 under 35 U.S.C. § 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, new grounds of rejection are made in view of U.S. Patent Application Publication No. 2018/0278821 A1 (“Yu”) and in view of U.S. Patent Application Publication No. 2013/0242120 A1 (“Venkatraman”). As will be shown in full below, Yu teaches adjusting a white balance (AWB) response time dependent on a camera motion mode that is determined based on a detected angular velocity or acceleration, and Venkatraman teaches reducing a threshold to recalculate AWB based on movement (Fig. 5, ¶ 0036). These are sufficient to teach the claimed color adaptation speed or AWB frequency update based on a detected rate of motion (threshold) as in the independent claims.
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, 2, 5–7, 9, 18, 19, 22, 24, and 28 are rejected under 35 U.S.C. § 103 as being unpatentable over U.S. Patent Application Publication No. 2015/0222799 A1 (“Noorkami”) in view of U.S. Patent Application Publication No. 2018/0278821 A1 (“Yu”).
Noorkami, directed to white balance, teaches with respect to claim 1:
A method of operating an electronic device having at least one image sensor (¶ 0040, electronic device 10 including camera 32) and at least one motion sensor (¶ 0040, electronic device 10 includes inertial sensor), the method comprising:
acquiring a video feed using the at least one image sensor (¶ 0035, Fig. 3, acquiring video frame);
detecting a . . . motion of the electronic device using the at least one motion sensor (id., computing camera movement); and
performing color correction on the video feed . . . based on the detected . . . motion of the electronic device to generate a corresponding color corrected video feed (id., automatic white balance as a result of distance travelled reaching or exceeding a threshold).
The present invention differs from Noorkami in that the claimed invention as amended specifies detecting a “rate of motion”, interpreted based on the specification at ¶ 0057 and the 25 July 2025 and 13 February 2026 interviews as an instantaneous rate of movement, speed, or an acceleration. Noorkami, in contrast, teaches detecting an accumulation of motion over time. However, Yu, directed to a camera, teaches with respect to claim 1:
detecting a rate of motion of the electronic device using the at least one motion sensor (¶ 0029, acceleration sensor within camera); and
performing color correction on the video feed by adjusting a color adaptation speed based on the detected rate of motion of the electronic device (¶ 0040–42, determining motion mode according to acceleration signal; ¶¶ 0034, 0066–67, varying auto white balance (AWB) speed based on motion mode).
It would have been obvious to one of ordinary skill in the art at the time of effective filing to modify the Noorkami camera to adjust white balance speed based on a motion mode, as taught by Yu, in order to increase the quality of the video captured. Yu ¶ 0007.
Regarding claim 2, Noorkami in view of Yu teaches the method of claim 1, further comprising:
displaying the color corrected video feed using one or more displays in the video device (Noorkami ¶¶ 0039, 0042; display 28 for user interface).
Regarding claim 5, Noorkami in view of Yu teaches the method of claim 3, further comprising:
in response to detecting a second rate of motion of the electronic device different than the first rate of motion, keeping constant the color adaptation speed of the color correction on the video feed (Yu Table TB2; ¶¶ 0056–61; constant AWB fast response in transition between tripod mode and still mode).
Regarding claim 6, Noorkami in view of Yu teaches the method of claim 1, further comprising:
determining whether a lighting condition in the video feed has changed (Noorkami ¶ 0032, determine if white balance or exposure changed beyond a threshold in addition to determining if distance travelled has reached a threshold);
in response to determining that the lighting condition in the video feed has changed, increasing a color adaptation speed of the color correction on the video feed (Noorkami ¶ 0037, create transition period between old and new settings for intermediate frames on applying new setting, by interpolating the old and new settings and applying them to intermediate frames); and
in response to determining that the lighting condition in the video feed has not changed, maintaining or decreasing the color adaptation speed of the color correction on the video feed (Noorkami ¶ 0035, not changing settings if the motion has not exceeded a threshold).
Regarding claim 7, Noorkami in view of Yu teaches the method of claim 6, further comprising:
performing color correction on the video feed based on previous color statistics and current color statistics (Noorkami ¶ 0037, in transition period, interpolation of previous settings and current settings).
Regarding claim 9, Noorkami in view of Yu teaches the method of claim 7, further comprising:
comparing the color statistics to the previous color statistics (Noorkami ¶ 0037, using both current and previous settings during transition period).
Regarding claim 18, Noorkami in view of Yu teaches a method of operating an electronic device having one or more image sensors (¶ 0040, electronic device including camera 32) and one or more motion sensors (id., electronic device includes inertial sensor), the method comprising:
capturing a video feed using the one or more image sensors (¶ 0035, Fig. 3; acquiring video frame);
detecting . . . motion using the one or more motion sensors (id., calculate camera movement with inertial sensor);
analyzing a lighting condition of the video feed (¶ 0035, recalculate white balance and auto exposure); and
performing color correction on the video feed based on the lighting condition in the video feed (id., apply new values for white balance and exposure settings),
wherein a color adaptation speed of the color correction on the video feed is adjusting in response to detecting . . . motion exceeds or falls below a threshold (¶ 0035, triggering white balance algorithm if the accumulated motion reaches or exceeds a threshold).
The present invention differs from Noorkami in that the claimed invention as amended specifies detecting a “rate of motion”, interpreted based on the specification at ¶ 0057 and the 25 July 2025 and 13 February 2026 interviews as an instantaneous rate of movement, speed, or an acceleration. Noorkami, in contrast, teaches detecting an accumulation of motion over time. However, Yu, directed to a camera, teaches with respect to claim 1:
detecting a rate of motion of the electronic device using the at least one motion sensor (¶ 0029, acceleration sensor within camera); and
performing color correction on the video feed . . . wherein a color adaptation speed of the color correction on the video feed is adjusted in respond to detecting that the rate of motion exceeds or falls below a threshold by adjusting a color adaptation speed based on the detected rate of motion of the electronic device (¶ 0040–42, determining motion mode according to acceleration signal; ¶¶ 0034, 0066–67, varying auto white balance (AWB) speed based on motion mode; e.g. ¶¶ 0056, 0080, mode selection based on threshold level of acceleration).
It would have been obvious to one of ordinary skill in the art at the time of effective filing to modify the Noorkami camera to adjust white balance speed based on a motion mode, as taught by Yu, in order to increase the quality of the video captured. Yu ¶ 0007.
Regarding claim 19, Noorkami in view of Yu teaches the method of claim 18, further comprising:
increasing the color adaptation speed in response to determining that the lighting condition has changed (Noorkami ¶ 0037, transition period has dynamic change in settings); and
maintaining or decreasing the color adaptation speed in response to determining that the lighting condition is stable (¶ 0035, not changing settings if the motion has not exceeded a threshold).
Regarding claim 22, Noorkami in view of Yu teaches the method of claim 18, further comprising:
maintaining or decreasing the color adaptation speed in response to detecting a lack of change in the rate of motion using the one or more motion sensors (Yu Table TB2; ¶¶ 0056–61; constant AWB fast response in transition between tripod mode and still mode).
Regarding claim 24, Noorkami in view of Yu teaches an electronic device comprising:
one or more image sensors configured to capture a video feed (¶ 0040, camera 32 in electronic device);
one or more motion sensors configured to detect motion (id., inertial sensor); and
control circuitry (Fig. 6, controller 22) configured to:
analyze a lighting condition of the captured video feed (id., camera exposure system 38), and
perform auto white balancing (AWB) operations on the captured video feed (¶ 0035, white balance),
wherein an update frequency of the AWB operations is determined based on the lighting condition (¶ 0032, determine whether white balance produces video changes over a threshold) and the detected rate of motion (Yu ¶ 0040–42, determining motion mode according to acceleration signal; ¶¶ 0034, 0066–67, varying auto white balance (AWB) speed based on motion mode).
Regarding claim 28, Noorkami in view of Yu teaches the method of claim 1, further comprising:
adjusting the color adaptation speed of the color correction on the video feed by correlating previous color statistics to current color statistics (Noorkami ¶ 0037, using both current and previous settings during transition period).
Claims 8, 10, 11, 14, 17, 20, 21, 25, and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Noorkami in view of Yu and in view of U.S. Patent Application Publication No. 2017/0034494 A1 (“Kang”).
Claims 10–17, 20, 21, and 27 recite or are dependent on claims that recite flicker detection. Noorkami and Yu do not teach this limitation.
Specifically regarding claim 10, Kang teaches the method of claim 6, further comprising:
performing color correction on the video feed based on data obtained from a flicker detection sensor in the electronic device (Abstract, white balance based on flicker analysis).
It would have been obvious to one of ordinary skill in the art at the time of effective invention to modify the Noorkami or Yu white balance to take into account flicker analysis, as taught by Kang, in order to improve white balance from a scene illuminated with a variety of light source types, such as incandescent lamps and fluorescent lamps that have a frequency of 50 Hz or 60 Hz. Kang ¶¶ 0006–07.
Regarding claim 11, Noorkami in view of Yu and Kang teaches the method of claim 10, wherein the data obtained from the flicker detection sensor comprises frequency information about lighting in the video feed (Kang ¶ 0006–07, recognizing lamps with 50 Hz or 60 Hz frequency).
Regarding claim 14, Noorkami in view of Yu and Kang teaches the method of claim 10, wherein the data obtained form the flicker detection sensor comprises:
a first channel output that includes only visible light measurements (Kang Fig. 5, output from image sensor 210); and
a second channel output that includes only infrared light measurements (id., output from infrared sensor 143).
Regarding claim 17, Noorkami in view of Yu and Kang teaches the method of claim 1, further comprising:
computing a mixed lighting score indicative of a number or type of illuminants in the video feed (Kang Fig. 8, ¶ 0138; step S740 of determining white balance based on whether image is illuminated by solar light, a flickering light source that generates infrared, or a flickering light source that does not generate infrared); . . .
in response to determining that the mixed lighting score has a second value different than the first value, adjusting the color adaptation speed of the color correction on the video feed (Noorkami ¶ 0037, changing white balance over time by interpolating old and new white balance parameters).
Regarding claim 21, Noorkami in view of Yu and Kang teaches the method of claim 18, further comprising:
adjusting the color adaptation speed based on data from a flicker detection sensor in the electronic device (Kang Abstract, white balance based on flicker analysis; Noorkami ¶ 0037, changing white balance over time by interpolating old and new white balance parameters).
Regarding claim 8, Noorkami in view of Yu and Kang teaches the method of claim 7, further comprising:
filtering the previous color statistics spatially or in a time domain from a plurality of video feeds (Kang Fig. 5, outputs from image sensor and infrared sensor).
Regarding claim 20, Noorkami in view of Yu and Kang teaches the method of claim 18, further comprising:
increasing the color adaptation speed in response to determining that the video feed includes a first number of illuminants (Kang ¶ 0160, white source balance according to the ratio of plurality of light sources); and
maintaining or decreasing the color adaptation speed in response to determining that the video feed includes a second number of illuminants less than the first number of illuminants (Kang e.g. ¶ 0106, determining that only solar light exists).
Regarding claim 25, Noorkami in view of Yu and Kang teaches the method of claim 18, further comprising: computing a mixed lighting score indicative of a number or type of illuminants in the video feed (Kang Fig. 8, ¶ 0138; step S740 of determining white balance based on whether image is illuminated by solar light, a flickering light source that generates infrared, or a flickering light source that does not generate infrared); . . .
in response to determining that the mixed lighting score has a second value different than the first value, adjusting the color adaptation speed of the color correction on the video feed (Noorkami ¶ 0037, changing white balance over time by interpolating old and new white balance parameters).
Regarding claim 27, Noorkami in view of Yu and Kang teaches the method of claim 1, further comprising:
adjusting the color adaptation speed based on data from a flicker detection sensor in the electronic device (Kang Abstract, white balance based on flicker analysis; Noorkami ¶ 0037, changing white balance over time by interpolating old and new white balance parameters), wherein the data obtained from the flicker detection sensor comprises:
a first channel output that includes light measurements within a first range of wavelengths (Kang Fig. 5, output from image sensor 210); and
a second channel output that includes light measurements within a second range of wavelengths different from the first range of wavelengths. (id., output from infrared sensor 143).
Claim 26 is rejected under 35 U.S.C. § 103 as being unpatentable over Noorkami in view of Yu and in view of U.S. Patent Application Publication No. 2013/0242120 A1 (“Venkatraman”).
Claim 26 specifies adjusting the color adaptation speed such that it is proportional to the detected rate of motion. Yu, in contrast, calls for a fast AWB response in a tripod or still mode and slower responses in motion mode. Yu ¶ 0066. However, Venkatraman, directed to adjusting a camera state based on a motion state, teaches with respect to claim 26:
wherein adjusting the color adaptation speed based on the detected rate of motion of the electronic device further comprises adjusting the color adaptation speed by an amount that is proportional to the detected rate of motion of the electronic device (Fig. 5, threshold to recalculate white balance is reduced if user is moving).
It would have been obvious to one of ordinary skill in the art at the time of effective invention to modify Noorkami or Yu to use rapid AWB adjustment for higher speed, as taught by Venkatraman, in order to account for a more rapid scene composition change. Venkatraman ¶ 0066.
Claims 1, 2, 5–7, 9, 18, 19, 22, 24, 26, and 28 are rejected under 35 U.S.C. § 103 as being unpatentable over U.S. Patent Application Publication No. 2015/0222799 A1 (“Noorkami”) in view of U.S. Patent Application Publication No. 2013/242120 A1 (“Venkatraman”).
Noorkami, directed to white balance, teaches with respect to claim 1:
A method of operating an electronic device having at least one image sensor (¶ 0040, electronic device 10 including camera 32) and at least one motion sensor (¶ 0040, electronic device 10 includes inertial sensor), the method comprising:
acquiring a video feed using the at least one image sensor (¶ 0035, Fig. 3, acquiring video frame);
detecting a . . . motion of the electronic device using the at least one motion sensor (id., computing camera movement); and
performing color correction on the video feed . . . based on the detected . . . motion of the electronic device to generate a corresponding color corrected video feed (id., automatic white balance as a result of distance travelled reaching or exceeding a threshold).
The present invention differs from Noorkami in that the claimed invention as amended specifies detecting a “rate of motion”, interpreted based on the specification at ¶ 0057 and the 25 July 2025 and 13 February 2026 interviews as an instantaneous rate of movement, speed, or an acceleration. Noorkami, in contrast, teaches detecting an accumulation of motion over time. However, Venkatraman, directed to adjusting a camera state based on a motion state, teaches with respect to claim 1:
detecting a rate of motion of the electronic device using the at least one motion sensor (¶ 0036, Fig. 5; motion state classification); and
performing color correction on the video feed by adjusting a color adaptation speed based on the detected rate of motion of the electronic device (id., reducing threshold to recalculate AWB if user is moving).
It would have been obvious to one of ordinary skill in the art at the time of effective invention to modify Noorkami to use rapid AWB adjustment for higher speed, as taught by Venkatraman, in order to account for a more rapid scene composition change. Venkatraman ¶ 0066.
Regarding claim 2, Noorkami in view of Venkatraman teaches the method of claim 1, further comprising:
displaying the color corrected video feed using one or more displays in the video device (Noorkami ¶¶ 0039, 0042; display 28 for user interface).
Regarding claim 5, Noorkami in view of Venkatraman teaches the method of claim 3, further comprising:
in response to detecting a second rate of motion of the electronic device different than the first rate of motion, keeping constant the color adaptation speed of the color correction on the video feed (Venkatraman Fig. 5, binary determination of motion or not motion, regardless of speed).
Regarding claim 6, Noorkami in view of Venkatraman teaches the method of claim 1, further comprising:
determining whether a lighting condition in the video feed has changed (Noorkami ¶ 0032, determine if white balance or exposure changed beyond a threshold in addition to determining if distance travelled has reached a threshold);
in response to determining that the lighting condition in the video feed has changed, increasing a color adaptation speed of the color correction on the video feed (Noorkami ¶ 0037, create transition period between old and new settings for intermediate frames on applying new setting, by interpolating the old and new settings and applying them to intermediate frames); and
in response to determining that the lighting condition in the video feed has not changed, maintaining or decreasing the color adaptation speed of the color correction on the video feed (Noorkami ¶ 0035, not changing settings if the motion has not exceeded a threshold).
Regarding claim 7, Noorkami in view of Venkatraman teaches the method of claim 6, further comprising:
performing color correction on the video feed based on previous color statistics and current color statistics (Noorkami ¶ 0037, in transition period, interpolation of previous settings and current settings).
Regarding claim 9, Noorkami in view of Venkatraman teaches the method of claim 7, further comprising:
comparing the color statistics to the previous color statistics (Noorkami ¶ 0037, using both current and previous settings during transition period).
Regarding claim 18, Noorkami in view of Venkatraman teaches a method of operating an electronic device having one or more image sensors (¶ 0040, electronic device including camera 32) and one or more motion sensors (id., electronic device includes inertial sensor), the method comprising:
capturing a video feed using the one or more image sensors (¶ 0035, Fig. 3; acquiring video frame);
detecting . . . motion using the one or more motion sensors (id., calculate camera movement with inertial sensor);
analyzing a lighting condition of the video feed (¶ 0035, recalculate white balance and auto exposure); and
performing color correction on the video feed based on the lighting condition in the video feed (id., apply new values for white balance and exposure settings),
wherein a color adaptation speed of the color correction on the video feed is adjusting in response to detecting . . . motion exceeds or falls below a threshold (¶ 0035, triggering white balance algorithm if the accumulated motion reaches or exceeds a threshold).
The present invention differs from Noorkami in that the claimed invention as amended specifies detecting a “rate of motion”, interpreted based on the specification at ¶ 0057 and the 25 July 2025 and 13 February 2026 interviews as an instantaneous rate of movement, speed, or an acceleration. Noorkami, in contrast, teaches detecting an accumulation of motion over time. However, Venkatraman, directed to adjusting a camera state based on a motion state, teaches with respect to claim 18:
The present invention differs from Noorkami in that the claimed invention as amended specifies detecting a “rate of motion”, interpreted based on the specification at ¶ 0057 and the 25 July 2025 and 13 February 2026 interviews as an instantaneous rate of movement, speed, or an acceleration. Noorkami, in contrast, teaches detecting an accumulation of motion over time. However, Venkatraman, directed to adjusting a camera state based on a motion state, teaches with respect to claim 17:
detecting a rate of motion using one or more motion sensors (Abstract, ¶ 0006; determining user context state such as walking or standing from data from one or more sensors); and
performing color correction on the video feed based on the lighting condition in the video feed (¶ 0036, Fig. 5; AWB), wherein a color adaptation speed of the color correction on the video feed is adjusted in response to detecting that the rate of motion exceeds or falls below a threshold (id., reducing threshold to recalculate AWB if user is moving and increasing threshold if user is stationary).
It would have been obvious to one of ordinary skill in the art at the time of effective invention to modify Noorkami to use rapid AWB adjustment for higher speed, as taught by Venkatraman, in order to account for a more rapid scene composition change. Venkatraman ¶ 0066.
Regarding claim 19, Noorkami in view of Venkatraman teaches the method of claim 18, further comprising:
increasing the color adaptation speed in response to determining that the lighting condition has changed (Noorkami ¶ 0037, transition period has dynamic change in settings); and
maintaining or decreasing the color adaptation speed in response to determining that the lighting condition is stable (¶ 0035, not changing settings if the motion has not exceeded a threshold).
Regarding claim 22, Noorkami in view of Venkatraman teaches the method of claim 18, further comprising:
maintaining or decreasing the color adaptation speed in response to detecting a lack of change in the rate of motion using the one or more motion sensors (Venkatraman Fig. 5, ¶ 0036; binary determination of motion or no motion, not change in motion speed).
Regarding claim 24, Noorkami in view of Venkatraman teaches an electronic device comprising:
one or more image sensors configured to capture a video feed (Noorkami ¶ 0040, camera 32 in electronic device);
one or more motion sensors configured to detect motion (id., inertial sensor); and
control circuitry (Fig. 6, controller 22) configured to:
analyze a lighting condition of the captured video feed (id., camera exposure system 38), and
perform auto white balancing (AWB) operations on the captured video feed (¶ 0035, white balance),
wherein an update frequency of the AWB operations is determined based on the lighting condition (¶ 0032, determine whether white balance produces video changes over a threshold) and the detected rate of motion (Venkatraman Fig. 5, ¶ 0036; changing the threshold to recalculate AWB based on whether motion is detected).
Regarding claim 26, Noorkami in view of Venkatraman teaches the method of claim 1, wherein adjusting the color adaptation speed based on the detected rate of motion of the electronic device (Venkatraman Fig. 5, ¶ 0036; reducing threshold to recalculate AWB if motion is detected and increasing threshold if no motion is detected).
Regarding claim 28, Noorkami in view of Venkatraman teaches the method of claim 1, further comprising:
adjusting the color adaptation speed of the color correction on the video feed by correlating previous color statistics to current color statistics (Noorkami ¶ 0037, using both current and previous settings during transition period).
Claims 8, 10, 11, 14, 17, 20, 21, 25, and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Noorkami in view of Venkatraman and in view of U.S. Patent Application Publication No. 2017/0034494 A1 (“Kang”).
Claims 10–17, 20, 21, and 27 recite or are dependent on claims that recite flicker detection. Noorkami and Yu do not teach this limitation.
Specifically regarding claim 10, Kang teaches the method of claim 6, further comprising:
performing color correction on the video feed based on data obtained from a flicker detection sensor in the electronic device (Abstract, white balance based on flicker analysis).
It would have been obvious to one of ordinary skill in the art at the time of effective invention to modify the Noorkami or Venkatraman white balance to take into account flicker analysis, as taught by Kang, in order to improve white balance from a scene illuminated with a variety of light source types, such as incandescent lamps and fluorescent lamps that have a frequency of 50 Hz or 60 Hz. Kang ¶¶ 0006–07.
Regarding claim 11, Noorkami in view of Venkatraman and Kang teaches the method of claim 10, wherein the data obtained from the flicker detection sensor comprises frequency information about lighting in the video feed (Kang ¶ 0006–07, recognizing lamps with 50 Hz or 60 Hz frequency).
Regarding claim 14, Noorkami in view of Venkatraman and Kang teaches the method of claim 10, wherein the data obtained form the flicker detection sensor comprises:
a first channel output that includes only visible light measurements (Kang Fig. 5, output from image sensor 210); and
a second channel output that includes only infrared light measurements (id., output from infrared sensor 143).
Regarding claim 17, Noorkami in view of Venkatraman and Kang teaches the method of claim 1, further comprising:
computing a mixed lighting score indicative of a number or type of illuminants in the video feed (Kang Fig. 8, ¶ 0138; step S740 of determining white balance based on whether image is illuminated by solar light, a flickering light source that generates infrared, or a flickering light source that does not generate infrared); . . .
in response to determining that the mixed lighting score has a second value different than the first value, adjusting the color adaptation speed of the color correction on the video feed (Noorkami ¶ 0037, changing white balance over time by interpolating old and new white balance parameters).
Regarding claim 21, Noorkami in view of Venkatraman and Kang teaches the method of claim 18, further comprising:
adjusting the color adaptation speed based on data from a flicker detection sensor in the electronic device (Kang Abstract, white balance based on flicker analysis; Noorkami ¶ 0037, changing white balance over time by interpolating old and new white balance parameters).
Regarding claim 8, Noorkami in view of Venkatraman and Kang teaches the method of claim 7, further comprising:
filtering the previous color statistics spatially or in a time domain from a plurality of video feeds (Kang Fig. 5, outputs from image sensor and infrared sensor).
Regarding claim 20, Noorkami in view of Venkatraman and Kang teaches the method of claim 18, further comprising:
increasing the color adaptation speed in response to determining that the video feed includes a first number of illuminants (Kang ¶ 0160, white source balance according to the ratio of plurality of light sources); and
maintaining or decreasing the color adaptation speed in response to determining that the video feed includes a second number of illuminants less than the first number of illuminants (Kang e.g. ¶ 0106, determining that only solar light exists).
Regarding claim 25, Noorkami in view of Venkatraman and Kang teaches the method of claim 18, further comprising: computing a mixed lighting score indicative of a number or type of illuminants in the video feed (Kang Fig. 8, ¶ 0138; step S740 of determining white balance based on whether image is illuminated by solar light, a flickering light source that generates infrared, or a flickering light source that does not generate infrared); . . .
in response to determining that the mixed lighting score has a second value different than the first value, adjusting the color adaptation speed of the color correction on the video feed (Noorkami ¶ 0037, changing white balance over time by interpolating old and new white balance parameters).
Regarding claim 27, Noorkami in view of Venkatraman and Kang teaches the method of claim 1, further comprising:
adjusting the color adaptation speed based on data from a flicker detection sensor in the electronic device (Kang Abstract, white balance based on flicker analysis; Noorkami ¶ 0037, changing white balance over time by interpolating old and new white balance parameters), wherein the data obtained from the flicker detection sensor comprises:
a first channel output that includes light measurements within a first range of wavelengths (Kang Fig. 5, output from image sensor 210); and
a second channel output that includes light measurements within a second range of wavelengths different from the first range of wavelengths. (id., output from infrared sensor 143).
Allowable Subject Matter
Claims 12 and 13 are allowed.
Claim 16 is 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
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The following prior art was found using an Artificial Intelligence assisted search using an internal AI tool that uses the classification of the application under the Cooperative Patent Classification (CPC) system, as well as from the specification, including the claims and abstract, of the application as contextual information. The documents are ranked from most to least relevant. Where possible, English-language equivalents are given, and redundant results within the same patent families are eliminated. See “New Artificial Intelligence Functionality in PE2E Search”, 1504 OG 359 (15 November 2022), “Automated Search Pilot Program”, 90 F.R. 48,161 (8 October 2025).
US 2022/0254115 A1
US 2010/0277485 A1
US 2019/0139281 A1
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