Prosecution Insights
Last updated: October 02, 2026
Application No. 18/546,520

BEHAVIOR RECOGNITION IN AN ENCLOSURE

Final Rejection §103
Filed
Aug 15, 2023
Priority
Dec 22, 2009 — provisional 61/289,319 +48 more
Examiner
SURVILLO, OLEG
Art Unit
2457
Tech Center
2400 — Computer Networks
Assignee
View Inc.
OA Round
4 (Final)
72%
Grant Probability
Favorable
5-6
OA Rounds
1y 2m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allowance Rate
421 granted / 581 resolved
+14.5% vs TC avg
Strong +29% interview lift
Without
With
+29.2%
Interview Lift
resolved cases with interview
Typical timeline
4y 3m
Avg Prosecution
17 currently pending
Career history
601
Total Applications
across all art units

Statute-Specific Performance

§101
11.5%
-28.5% vs TC avg
§103
48.5%
+8.5% vs TC avg
§102
13.0%
-27.0% vs TC avg
§112
23.8%
-16.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 581 resolved cases

Office Action

§103
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Response to Amendment Claims 78, 80-91, 94-96, and 99 are pending in the application. Claims 78 and 96 are currently amended. Claims 1-77, 79, 92-93, and 97-98 have been canceled. Claim 99 is new. Response to Arguments With regard to Applicant’s remarks dated June 25, 2026: Regarding the objection to claims 78 and 96, Applicant’s amendment has been fully considered and is sufficient. Therefore, the rejection has been withdrawn. Regarding the rejection of claims 78-91, 94-96, and 98 under 35 U.S.C. 103, Applicant’s amendment and arguments have been fully considered. Applicants argue that “Hwang does not teach comparison of any behavior between known users, much less "a comparison between the unique external behavior by the known users and external behavior of at least one other user of the known users " Nor does Hwang teach "determining whether external behavior by the known users is the unique external behavior of the known users by a comparison of the external behavior by the known user to the external behavior of the at least one other user of the known users." Rather Hwang looks for a predetermined type of behavior, such as a typical gait, pose, or movement”. Examiner agrees. Therefore, the rejection has been withdrawn. However, new grounds of rejection are made in view of the newly discovered references. As to any arguments not specifically addressed, they are the same as those discussed above. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 78, 80-91, 94-96, and 99 are rejected under 35 U.S.C. 103 as being unpatentable over Tusch et al. (US 2021/0279475 A1) in view of Hwang et al. (US 2022/0210341 A1) and in further view of Hazelwood et al. (US Patent 10,929,829 B1). As to claim 78, Tusch teaches a method for external behavior recognition for control of an environment of a facility [smart home automation] (par. [0118]-[0121], [0391]), the method comprising: training a behavior learning module with unique external behavior exhibited by known users [training ART platform by creating person’s own digital avatar that is programmed with a specific person’s gesture but not someone else’s to be recognized in operation] (par. [0315]-[0316], [0391], [0442], [1010]); capturing, with an imaging system of the facility, a plurality of successive images of a user of the facility (Figs. 9, 11, 18, 60, par. [0344], [0349], [0431]); obtaining, from the plurality of successive images, external behavior data of the user, wherein the external behavior data is representative of one or more physical actions taken by the user during the capturing of the plurality of successive images [people trajectory, pose, gesture, identity generation] (Fig. 18, par. [0289], [0356], [0357]); determining an identity of the user as one of the known users based at least in part on the external behavior data of the user by the behavior learning module trained with the unique external behavior exhibited by the known users [identity+gesture=control. Performing identification of a known user and what they are trying to do that is specific to that known user] (par. [0421]-[0422], [0441]-[0442]); and implementing environment customizations associated with the identity of the user [creating ART events such as customized temperature control for the detected individual or allowing an adult to turn on/off smoke alarm, but not kids] (Fig. 43, par. [0421]-[0422], [0738]). Tusch fails to expressly teach that the unique external behavior exhibited by the known users includes a user-specific movement pattern determined from a series of physical actions performed by each respective known user. Hwang is directed to performing a user-specific customization associated with the user identifier based on determining multiple biometric characteristics of the person and associating the characteristics with a user identifier unique to the person (abstract). In particular, Hwang teaches an external behavior exhibited by the known users includes a user-specific movement pattern determined from a series of physical actions performed by each respective known user [typical gaits, poses, gestures, and other movements that can be used to identify particular persons in order to apply appropriate customizations] (par. [0006], [0022], [0040], [0047], [0095]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method and system of Tusch by having the unique external behavior exhibited by the known users include a user-specific movement pattern determined from a series of physical actions performed by each respective known user in order to recognize and track the person within the environment based on biometric characteristics other than a facial recognition result (par. [0040] in Hwang). Tusch in view of Hwang fails to teach that the unique external behavior exhibited by the known users is based on a comparison between the unique external behavior by the known users and the external behavior of at least one other user of the known users. Hazelwood is directed to providing an identity verification and account association utilizing the gait of a customer (abstract). In particular, Hazelwood teaches determining a unique external behavior exhibited by the known users [a person’s gait is determined at least in part by a unique combination of a large number of personal characteristics that would unlikely be replicable] (col. 4 line 53 to col. 5 line 8) based on a comparison between the unique external behavior by the known users and the external behavior of at least one other user of the known users [matching a gait signature of a particular user with stored gait signatures including signatures of other registered users, where the detected gait signature is compared to a plurality of stored gait signatures until a match is detected] (col. 8 line 58 to col. 9 line 12). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method and system of Tusch in view of Hwang by determining the unique external behavior exhibited by the known users based on a comparison between the unique external behavior by the known users and the external behavior of at least one other user of the known users in order to identify the user based on the person’s gait that is generally unique to the individual (col. 2 lines 5-21 in Hazelwood). As to claim 80, Tusch teaches that the imaging system comprises a camera, an infrared (IR) camera, a lidar sensor, or an imaging radar system (Fig. 7). As to claim 81, Tusch teaches that obtaining the external behavior data of the user comprises extracting a respective pose of the user from each image of the plurality of successive images [extracting a pose of the individual] (par. [0413], [0431]). As to claim 82, Tusch teaches that determining the identity of the user based at least in part on the external behavior data of the user comprises determining a unique identifier associated with the user [unique identity] (par. [0093]). As to claim 83, Tusch teaches that implementing environment customizations comprises controlling an environmental aspect using one or more building systems (Fig. 43, par. [0738]). As to claim 84, Tusch teaches that the one or more building systems comprise a tintable window [non-functional descriptive material. It is well known for a home to have windows that can be tinted. The claim does not require any action with respect to a window] (par. [0478]). As to claim 85, Tusch teaches that implementing the environment customizations comprises adjusting a temperature, window tint, and/or lighting within the facility (Fig. 43, par. [0738]). As to claim 86, Tusch teaches that capturing the plurality of successive images of the user is responsive to a triggering event [event trigger basis] (par. [0945]). As to claim 87, Tusch teaches that the triggering event comprises detection of the user at a location of the facility (par. [0945]). As to claim 88, Tusch teaches that determining the identity of the user is further based on sensor information regarding the user [face or iris recognition using a sensor] (par. [0346], [1022]). As to claim 89, Tusch teaches that the sensor information comprises information indicative of a sound made by the user, dimensions of the user, and/or biometric information regarding the user [face or iris recognition using a sensor] (par. [0346], [1022]). As to claim 90, Tusch teaches that determining the identity of the user is further based on one or more device inputs received from the user [voice recognition] (par. [1018]-[1020]). As to claim 91, Tusch teaches that the one or more device inputs comprise a temperature setting, a window tint setting, and/or a lighting setting [voice control system within the home] (par. [0186], [0194]). As to claim 94, Tusch teaches that training the behavior learning module comprises using previously-obtained sets of images of the known users taking the one or more physical actions as a positive dataset [the system is trained using a large dataset of normal behavior of users and uses it to flag abnormal behavior in operation] (par. [1014], [1035]). As to claim 95, Tusch teaches that the previously-obtained sets of images are obtained by the imaging system (par. [1011]-[1013]). As to claim 96, Tusch in view of Hwang and Hazelwood teaches an apparatus for external behavior recognition for control of an environment of a facility [computer-vision system] (par. [1057] in Tusch), the apparatus comprising one or more controllers comprising circuitry (par. [0323]-[0325] in Tusch), which one or more controllers are configured to perform the method steps as discussed per claim 78, above. As to claim 99, Tusch in view of Hwang and Hazelwood teaches determining whether external behavior by the known users is the unique external behavior of the known users [a person’s gait is determined at least in part by a unique combination of a large number of personal characteristics that would unlikely be replicable] (col. 4 line 53 to col. 5 line 8 in Hazelwood) by a comparison of the external behavior by the known user to the external behavior of the at least one other user of the known users [matching a gait signature of a particular user with stored gait signatures including signatures of other registered users, where the detected gait signature is compared to a plurality of stored gait signatures until a match is detected] (col. 8 line 58 to col. 9 line 12 in Hazelwood). Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to OLEG SURVILLO whose telephone number is (571)272-9691. The examiner can normally be reached 9:00am - 5:00pm. Examiner interviews are available via telephone, in-person, 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. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ario Etienne can be reached at 571-272-4001. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. 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. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /OLEG SURVILLO/Primary Examiner, Art Unit 2457
Read full office action

Prosecution Timeline

Show 1 earlier event
May 30, 2025
Non-Final Rejection mailed — §103
Aug 25, 2025
Response Filed
Dec 02, 2025
Final Rejection mailed — §103
Feb 26, 2026
Request for Continued Examination
Mar 08, 2026
Response after Non-Final Action
Mar 25, 2026
Non-Final Rejection mailed — §103
Jun 25, 2026
Response Filed
Sep 16, 2026
Final Rejection mailed — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12745052
PLAYBACK TRANSITIONS
1y 10m to grant Granted Sep 22, 2026
Patent 12737768
DATA TRANSFER ACROSS LAYER 2 NETWORKS
2y 10m to grant Granted Sep 15, 2026
Patent 12732505
AUTHORIZATION LEVEL UNLOCK FOR MATCHING AUTHORIZATION CATEGORIES
1y 7m to grant Granted Sep 08, 2026
Patent 12706097
SYNCHRONIZATION OF REMOTE CONTEXT DATA
1y 10m to grant Granted Aug 11, 2026
Patent 12687828
Process Data Exchange with Guaranteed Minimum Transmission Intervals
3y 6m to grant Granted Jul 21, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

Strategy Recommendation AI-generated — please review before filing

Get a prosecution strategy drawn from examiner precedents, rejection analysis, and claim mapping.
Typically takes 5-10 seconds — AI-generated, attorney review required before filing

Prosecution Projections

5-6
Expected OA Rounds
72%
Grant Probability
99%
With Interview (+29.2%)
4y 3m (~1y 2m remaining)
Median Time to Grant
High
PTA Risk
Based on 581 resolved cases by this examiner. Grant probability derived from career allowance rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month