IP Library › Granted Patent US 12,244,784
Granted Patent B2
US 12,244,784 · App. 16/937,884 · Granted Mar 4, 2025

Multiview interactive digital media representation inventory verification

Inventors: Keith George Martin (San Francisco, CA); Dave Morrison (San Francisco, CA); Stefan Johannes Josef Holzer (San Mateo, CA); Radu Bogdan Rusu (San Francisco, CA)
Assignee: Fyusion, Inc.
H04N13/282G06V20/52G06V20/64H04N13/275G06V20/625G06V2201/08
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,244,784
App. No.
16/937,884
Filed
Jul 24, 2020
Granted
Mar 4, 2025
Kind
B2
Art Unit
2662
USPC
382/154
Abstract

Inventory at a remote location may be verified by transmitting a security key associated with uniquely identifying object identification information from a verification server to a client machine at the remote location. The security key may then be used to generate a multi-view interactive digital media representation (MVIDMR) of the object that includes a plurality of images captured from different viewpoints. The MVIDMR may then be transmitted to the verification server.

Claims (41)

1. A computing device comprising:

a camera operable to capture an image of object identification information uniquely identifying an object in physical proximity to a client machine;

a communication interface operable to transmit the object identification information to a remote server and to receive from the server a security key associated with the object;

generating a watermark using the security key;

a processor operable to generate a multi-view interactive digital media representation (MVIDMR), the MVIDMR including a plurality of images of the object captured via the camera, each of the images being captured from a respective viewpoint, the viewpoints corresponding to the movement of the computing device through space in proximity to the object, the MVIDMR including the watermark generated using the security key, wherein the MVIDMR is transmitted to the remote server via the communication interface, wherein the server verifies that the computing device is located where the object is supposed to be located and that the MVIDMR is generated in the time period between when the security key is sent and the time when the MVIDMR is received by the server; and

a display screen via which the MVIDMR is navigable in one or more dimensions.

2. The computing device recited in claim 1 , wherein:

inertial measurement unit (IMU) data is captured from an IMU located within the client machine.

3. The computing device recited in claim 2 , wherein the IMU includes one or more accelerometers, and wherein the IMU data includes information characterizing acceleration of the client machine through space during various periods of time.

4. The computing device recited in claim 2 , wherein the MVIDMR is generated in part based on the IMU data.

5. The computing device recited in claim 4 , wherein generating the MVIDMR comprises positioning the images with respect to each other based in part on the IMU data.

6. The computing device recited in claim 1 , wherein the communication interface is further operable to transmit geolocation information to the remote server.

7. The computing device recited in claim 6 , wherein the geolocation information includes global positioning system (GPS) coordinates.

8. The computing device recited in claim 1 , wherein the movement of the computing device through space comprises a 360-degree arc around the object.

9. The computing device recited in claim 1 , wherein generating the MVIDMR comprises:

identifying a plurality of key points associated with the object;

for each of the images, determining respective locations for one or more of the key points in the image; and

positioning the images with respect to each other based in part on the key point locations.

10. The computing device recited in claim 1 , wherein the object is a vehicle, and wherein the object identification information comprises a vehicle identification number (VIN).

11. The computing device recited in claim 10 , wherein transmitting the object identification information comprises transmitting a picture of a VIN plate on a vehicle dashboard.

12. A method comprising:

transmitting object identification information from a client machine to a remote verification server, the object identification information uniquely identifying an object in physical proximity to the client machine;

receiving from the server a security key associated with the object;

generating a watermark using the security key;

generating at the client machine a multi-view interactive digital media representation (MVIDMR), the MVIDMR including a plurality of images of the object, each of the images being captured from a respective viewpoint, the viewpoints corresponding to the movement of the client machine through space in proximity to the object, the MVIDMR including the watermark generated using the security key, the MVIDMR being navigable in one or more dimensions via a user interface at the client machine; and

transmitting the MVIDMR to the remote verification server, wherein the server verifies that the computing device is located where the object is supposed to be located and that the MVIDMR is generated in the time period between when the security key is sent and the time when the MVIDMR is received by the server.

13. The method recited in claim 12 , the method further comprising:

capturing inertial measurement unit (IMU) data from an IMU located within the client machine.

14. The method recited in claim 13 , wherein the IMU includes one or more accelerometers, and wherein the IMU data includes information characterizing acceleration of the client machine through space during various periods of time.

15. The method recited in claim 13 , wherein the MVIDMR is generated in part based on the IMU data.

16. The method recited in claim 12 , the method further comprising transmitting geolocation information to the verification server.

17. The method recited in claim 16 , wherein the geolocation information includes global positioning system (GPS) coordinates.

18. The method recited in claim 12 , wherein the movement of the computing device through space comprises a 360-degree arc around the object.

19. One or more non-transitory computer readable media having instructions stored thereon for performing a method, the method comprising:

transmitting object identification information from a client machine to a remote verification server, the object identification information uniquely identifying an object in physical proximity to the client machine;

receiving from the server a security key associated with the object;

generating a watermark using the security key;

generating at the client machine a multi-view interactive digital media representation (MVIDMR), the MVIDMR including a plurality of images of the object, each of the images being captured from a respective viewpoint, the viewpoints corresponding to the movement of the client machine through space in proximity to the object, the MVIDMR including the watermark generated using the security key, the MVIDMR being navigable in one or more dimensions via a user interface at the client machine; and

transmitting the MVIDMR to the remote verification server, wherein the server verifies that the computing device is located where the object is supposed to be located and that the MVIDMR is generated in the time period between when the security key is sent and the time when the MVIDMR is received by the server.

20. The one or more non-transitory computer readable media recited in claim 19 , the method further comprising:

capturing inertial measurement unit (IMU) data from an IMU located within the client machine, wherein the IMU includes one or more accelerometers, and wherein the IMU data includes information characterizing acceleration of the client machine through space during various periods of time, and wherein the MVIDMR is generated in part based on the IMU data.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 6, 2020
From: MARTIN, KEITH GEORGE; MORRISON, DAVE; HOLZER, STEFAN JOHANNES JOSEF; RUSU, RADU BOGDAN
To: FYUSION, INC.
Reel/Frame 053418/0593 →
Continuity (2)
Provisional Application 62879859 · Jul 29, 2019
Related Publication 20210037230A1 · Feb 4, 2021
References Cited (188)
US 5764306A · Steffano · 1998 [cited by applicant]
US 5923380A · Yang · 1999 [cited by applicant]
US 6067369A · Kamei · 2000 [cited by applicant]
US 6453069B1 · Matsugu · 2002 [cited by applicant]
US 6788309B1 · Swan · 2004 [cited by applicant]
US 6879956B1 · Honda · 2005 [cited by applicant]
US 6912313B2 · Li · 2005 [cited by applicant]
US 7042346B2 · Paulsen · 2006 [cited by applicant]
US 7249019B2 · Culy · 2007 [cited by applicant]
US 7292257B2 · Kang · 2007 [cited by applicant]
US 7565004B2 · Hashimoto · 2009 [cited by applicant]
US 7949529B2 · Weider · 2011 [cited by applicant]
US 9182229B2 · Grässer · 2015 [cited by applicant]
US 9218698B2 · Ricci · 2015 [cited by applicant]
US 9467750B2 · Banica · 2016 [cited by applicant]
US 9495764B1 · Boardman · 2016 [cited by applicant]
US 9886636B2 · Zhang · 2018 [cited by applicant]
US 9886771B1 · Chen · 2018 [cited by applicant]
US 10055708B2 · Kakarala et al. · 2018 [cited by applicant]
US 10319094B1 · Chen · 2019 [cited by applicant]
US 10373387B1 · Fields · 2019 [cited by applicant]
US 10515489B2 · Jefferies et al. · 2019 [cited by applicant]
US 10573012B1 · Collins · 2020 [cited by examiner]
US 10636148B1 · Chen · 2020 [cited by applicant]
US 10657647B1 · Chen · 2020 [cited by applicant]
US 10698558B2 · Holzer · 2020 [cited by applicant]
US 11004188B2 · Holzer · 2021 [cited by applicant]
US 20020063714A1 · Haas · 2002 [cited by applicant]
US 20020198713A1 · Franz · 2002 [cited by applicant]
US 20040258306A1 · Hashimoto · 2004 [cited by applicant]
US 20070253618A1 · Kim · 2007 [cited by applicant]
US 20080101656A1 · Barnes · 2008 [cited by applicant]
US 20080180436A1 · Kraver · 2008 [cited by applicant]
US 20090289957A1 · Sroka · 2009 [cited by applicant]
US 20100111370A1 · Black · 2010 [cited by applicant]
US 20100251101A1 · Haussecker · 2010 [cited by applicant]
US 20110218825A1 · Hertenstein · 2011 [cited by applicant]
US 20130297353A1 · Strange · 2013 [cited by applicant]
US 20140119604A1 · Mai · 2014 [cited by applicant]
US 20140172245A1 · Soles · 2014 [cited by applicant]
US 20150029304A1 · Park · 2015 [cited by applicant]
US 20150097931A1 · Hatzilias · 2015 [cited by applicant]
US 20150103170A1 · Nelson · 2015 [cited by applicant]
US 20150125049A1 · Taigman · 2015 [cited by applicant]
US 20150278987A1 · Mihara · 2015 [cited by applicant]
US 20150317527A1 · Graumann · 2015 [cited by applicant]
US 20150347845A1 · Benson · 2015 [cited by applicant]
US 20150365661A1 · Hayashi · 2015 [cited by applicant]
US 20160035096A1 · Rudow · 2016 [cited by applicant]
US 20170109930A1 · Holzer · 2017 [cited by applicant]
US 20170199647A1 · Richman · 2017 [cited by applicant]
US 20170208246A1 · Kimura · 2017 [cited by applicant]
US 20170277363A1 · Holzer · 2017 [cited by applicant]
US 20170293894A1 · Taliwal · 2017 [cited by applicant]
US 20180027178A1 · MacMillan · 2018 [cited by applicant]
US 20180160102A1 · Luo · 2018 [cited by applicant]
US 20180190017A1 · Mendez · 2018 [cited by applicant]
US 20180225858A1 · Ni · 2018 [cited by applicant]
US 20180260793A1 · Li · 2018 [cited by applicant]
US 20180293552A1 · Zhang · 2018 [cited by applicant]
US 20180315260A1 · Anthony · 2018 [cited by applicant]
US 20180322623A1 · Memo · 2018 [cited by applicant]
US 20180338126A1 · Trevor · 2018 [cited by applicant]
US 20180349746A1 · Vallespi-Gonzalez · 2018 [cited by applicant]
US 20190012394A1 · Endras · 2019 [cited by applicant]
US 20190035165A1 · Gausebeck · 2019 [cited by applicant]
US 20190066304A1 · Hirano · 2019 [cited by applicant]
US 20190073641A1 · Utke · 2019 [cited by applicant]
US 20190098277A1 · Takama · 2019 [cited by applicant]
US 20190116322A1 · Holzer · 2019 [cited by applicant]
US 20190147221A1 · Grabner · 2019 [cited by applicant]
US 20190147583A1 · Stefan · 2019 [cited by applicant]
US 20190164301A1 · Kim · 2019 [cited by applicant]
US 20190189007A1 · Herman · 2019 [cited by applicant]
US 20190196698A1 · Cohen · 2019 [cited by applicant]
US 20190197196A1 · Yang · 2019 [cited by applicant]
US 20190205086A1 · McNulty · 2019 [cited by applicant]
US 20190317519A1 · Chen · 2019 [cited by applicant]
US 20190318759A1 · Doshi · 2019 [cited by applicant]
US 20190335156A1 · Rusu · 2019 [cited by applicant]
US 20190349571A1 · Herman · 2019 [cited by applicant]
US 20190392569A1 · Finch · 2019 [cited by applicant]
US 20200111201A1 · Kuruvilla · 2020 [cited by examiner]
US 20200118342A1 · Varshney · 2020 [cited by applicant]
US 20200151860A1 · Safdarnejad · 2020 [cited by applicant]
US 20200231286A1 · Movsesian · 2020 [cited by applicant]
US 20200233892A1 · Calhoun · 2020 [cited by applicant]
US 20200234397A1 · Holzer · 2020 [cited by applicant]
US 20200234398A1 · Holzer · 2020 [cited by applicant]
US 20200234424A1 · Holzer · 2020 [cited by applicant]
US 20200234451A1 · Holzer · 2020 [cited by applicant]
US 20200234488A1 · Holzer · 2020 [cited by applicant]
US 20200236296A1 · Holzer · 2020 [cited by applicant]
US 20200236343A1 · Holzer · 2020 [cited by applicant]
US 20200257862A1 · Kar · 2020 [cited by applicant]
US 20200258309A1 · Holzer · 2020 [cited by applicant]
US 20200312028A1 · Charvat · 2020 [cited by applicant]
US 20200322546A1 · Carolus · 2020 [cited by applicant]
US 20200349757A1 · Holzer · 2020 [cited by applicant]
GB 2573170A · 2019 [cited by applicant]
WO 2016064921A1 · 2016 [cited by applicant]
WO 2017115149A1 · 2017 [cited by applicant]
WO 2017195228A1 · 2017 [cited by applicant]
WO 2019229912 · 2019 [cited by applicant]
WO 2020009948A1 · 2020 [cited by applicant]
WO 2020125726 · 2020 [cited by applicant]
WO 2020154096A1 · 2020 [cited by applicant]
Zhou, X. Q., H. K. Huang, and Shieh-Liang Lou. “Authenticity and integrity of digital mammography images.” IEEE transactions on medical imaging 20.8 (2001): 784-791. (Year: 2001). [cited by examiner]
Zhao, Jian. “Applying digital watermarking techniques to online multimedia commerce.” Proc. Int. Conf. on Imaging Science, Systems and Applications (CISSA'97). vol. 7. 1997. (Year: 1997). [cited by examiner]
Abd-Eldayem, Mohamed M. “A proposed security technique based on watermarking and encryption for digital imaging and communications in medicine.” Egyptian Informatics Journal 14.1 (2013): 1-13. (Year: 2013). [cited by examiner]
Aparna, Puvvadi, and Polurie Venkata Vijay Kishore. “A blind medical image watermarking for secure e-healthcare application using crypto-watermarking system.” Journal of Intelligent Systems 29.1 (2019): 1558-1575. (Year… [cited by examiner]
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Apr. 7, 2022 for U.S. Appl. No. 17/215,596 (pp. 1-9). [cited by applicant]
Office Action (Final Rejection) dated Apr. 19, 2022 for U.S. Appl. No. 16/692,219 (pp. 1-13). [cited by applicant]
Office Action (Non-Final Rejection) dated Apr. 14, 2022 for U.S. Appl. No. 17/144,879 (pp. 1-12). [cited by applicant]
Office Action (Non-Final Rejection) dated Sep. 20, 2021 for U.S. Appl. No. 16/861,100 (pp. 1-19). [cited by applicant]
Office Action (Final Rejection) dated Jan. 19, 2022 for U.S. Appl. No. 16/861,100 (pp. 1-19). [cited by applicant]
Office Action dated Jul. 26, 2021 for U.S. Appl. No. 16/518,558 (pp. 1-17). [cited by applicant]
International Search Report and Written Opinion for App. No. PCT/US2021/013431, dated May 6, 2021, 10 pages. [cited by applicant]
Office Action (Final Rejection) dated Nov. 9, 2021 for U.S. Appl. No. 16/518,558 (pp. 1-17). [cited by applicant]
Office Action (Non-Final Rejection) dated Mar. 29, 2022 for U.S. Appl. No. 16/518,558 (pp. 1-16). [cited by applicant]
Int'l Application Serial No. PCT/US20/12592, Int'l Search Report and Written Opinion dated Apr. 21, 2020. 9 pages. [cited by applicant]
Alberto Chavez-Aragon, et al., “Vision-Based Detection and Labelling of Multiple Vehicle Parts”, 2011 14th International IEEE Conference on Intelligent Transportation Systems Washington, DC, USA. Oct. 5-7, 2011, 6 pages. [cited by applicant]
Wenhao Lu, et al., “Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency”, arXiv:1406.2375v2 [cs.CV] Jun. 11, 2014, 12 pages. [cited by applicant]
Riza Alp Guler et al., “DensePose: Dense Human Pose Estimation In The Wild”, arXiv:1802.00434v1 [cs.CV] Feb. 1, 2018, 12 pages. [cited by applicant]
Gerd Lindner et al., “Structure-Preserving Sparsification of Social Networks”, arXiv:1505.00564vl [cs.SI] May 4, 2015, 8 pages. [cited by applicant]
Shubham Tulsiani and Jitendra Malik, “Viewpoints and Keypoints”, arXiv:1411.6067v2 [cs.CV] Apr. 26, 2015, 10 pages. [cited by applicant]
Jeff Donahue et al., “DeCAF: ADeep Convolutional Activation Feature for Generic Visual Recognition”, arXiv: 1310.153 vl [cs.CV] Oct. 6, 2013, 10 pages. [cited by applicant]
International Search Report and Written Opinion for App. No. PCT/US2021/013471, dated May 6, 2021, 10 pages. [cited by applicant]
International Search Report and Written Opinion for App. No. PCT/US2021/013472, dated May 11, 2021, 10 pages. [cited by applicant]
Office Action dated May 18, 2021 for U.S. Appl. No. 16/692,219 (pp. 1-13). [cited by applicant]
Office Action dated Jun. 14, 2021 for U.S. Appl. No. 16/518,570 (pp. 1-24). [cited by applicant]
Office Action dated Jul. 16, 2021 for U.S. Appl. No. 16/518,501 (pp. 1-23). [cited by applicant]
U.S. Appl. No. 16/518,501, CTFR—Final Rejection, Dec. 9, 2020, 16 pgs. [cited by applicant]
U.S. Appl. No. 16/518,501, Non-Final Rejection, Sep. 1, 2020, 15 pgs. [cited by applicant]
U.S. Appl. No. 16/518,501, Examiner Interview Summary Record (Ptol-413), Nov. 23, 2020, 2 pgs. [cited by applicant]
U.S. Appl. No. 16/518,512, Non-Final Rejection, Oct. 1, 2020, 24 pgs. [cited by applicant]
U.S. Appl. No. 16/518,512, Examiner Interview Summary Record (Ptol-413), Nov. 19, 2020, 3 pgs. [cited by applicant]
U.S. Appl. No. 16/518,512, Office Action Appendix, Nov. 19, 2020, 1 pg. [cited by applicant]
U.S. Appl. No. 16/518,558, Non-Final Rejection, Sep. 8, 2020, 14 pgs. [cited by applicant]
U.S. Appl. No. 16/518,585, Non-Final Rejection, Sep. 3, 2020, 13 pgs. [cited by applicant]
U.S. Appl. No. 16/596,516, Non-Final Rejection, Jun. 23, 2020, 37 pgs. [cited by applicant]
U.S. Appl. No. 16/596,516, Notice Of Allowance And Fees Due (Ptol-85), Sep. 21, 2020, 10 pgs. [cited by applicant]
U.S. Appl. No. 16/692,133, Non-Final Rejection, Jul. 24, 2020, 17 pgs. [cited by applicant]
U.S. Appl. No. 16/692,170, Non-Final Rejection, Nov. 20, 2020, 13 pgs. [cited by applicant]
U.S. Appl. No. 16/692,219, Non-Final Rejection, Dec. 8, 2020, 9 pgs. [cited by applicant]
U.S. Appl. No. 16/861,100, Non-Final Rejection, Oct. 8, 2020, 11 pgs. [cited by applicant]
U.S. Appl. No. 16/518,512, Notice of Allowance mailed Jan. 25, 2021, 7 pgs. [cited by applicant]
U.S. Appl. No. 16/518,512, Notice of Allowance mailed Dec. 16, 2020, 9 pgs. [cited by applicant]
U.S. Appl. No. 16/518,558, Examiner Interview Summary mailed Dec. 16, 2020, 1 pg. [cited by applicant]
U.S. Appl. No. 16/518,558, Final Office Action mailed Dec. 16, 2020, 16 pgs. [cited by applicant]
U.S. Appl. No. 16/518,570, Non-Final Office Action mailed Jan. 6, 2021, 17 pgs. [cited by applicant]
U.S. Appl. No. 16/518,585, Notice of Allowance mailed Dec. 14, 2020, 5 pgs. [cited by applicant]
U.S. Appl. No. 16/692,133, Notice of Allowance mailed Dec. 15, 2020, 7pgs. [cited by applicant]
U.S. Appl. No. 16/692,170, Notice of Allowance mailed Feb. 9, 2021, 8 pgs. [cited by applicant]
U.S. Appl. No. 16/861,100, Advisory Action mailed Jun. 10, 2021, 3 pgs. [cited by applicant]
U.S. Appl. No. 16/861,100, Examiner Interview Summary mailed Feb. 10, 2021, 2 pgs. [cited by applicant]
U.S. Appl. No. 16/861,100, Examiner Interview Summary mailed Jun. 10, 2021, 1 pg. [cited by applicant]
U.S. Appl. No.16/861,100, Examiner Interview Summary mailed Jun. 3, 2021, 2 pgs. [cited by applicant]
U.S. Appl. No. 16/861,100, Final Office Action mailed Feb. 26, 2021, 15 pgs. [cited by applicant]
Office Action (Final Rejection) dated Jun. 14, 2021 for U.S. Appl. No. 16/518,570 (pp. 1-23). [cited by applicant]
Office Action (Non-Final Rejection) dated Sep. 2, 2021 for U.S. Appl. No. 17/174,250 (pp. 1-22). [cited by applicant]
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Sep. 15, 2021 for U.S. Appl. No. 16/518,570 (pp. 1-8). [cited by applicant]
Office Action (Non-Final Rejection) dated Sep. 24, 2021 for U.S. Appl. No. 17/215,596 (pp. 1-14). [cited by applicant]
Office Action (Non-Final Rejection) dated Oct. 4, 2021 for U.S. Appl. No. 16/861,097 (pp. 1-15). [cited by applicant]
Office Action (Non-Final Rejection) dated Dec. 7, 2021 for U.S. Appl. No. 16/692,219 (pp. 1-12). [cited by applicant]
Office Action (Final Rejection) dated Dec. 7, 2021 for U.S. Appl. No. 16/518,501 (pp. 1-21). [cited by applicant]
Office Action (Final Rejection) dated Jan. 20, 2022 for U.S. Appl. No. 17/215,596 (pp. 1-16). [cited by applicant]
Office Action (Final Rejection) dated Jan. 19, 2022 for U.S. Appl. No. 16/861,097 (pp. 1-16). [cited by applicant]
Office Action (Final Rejection) dated Mar. 3, 2022 for U.S. Appl. No. 17/174,250 (pp. 1-24). [cited by applicant]
Office Action (Non-Final Rejection) dated Mar. 28, 2022 for U.S. Appl. No. 16/518,501 (pp. 1-21). [cited by applicant]
Office Action (Non-Final Rejection) dated Jun. 15, 2022 for U.S. Appl. No. 16/861,097 (pp. 1-17). [cited by applicant]
Office Action (Non-Final Rejection) dated Jun. 15, 2022 for U.S. Appl. No. 16/861,100 (pp. 1-18). [cited by applicant]
Office Action (Non-Final Rejection) dated Jul. 22, 2022 for U.S. Appl. No. 17/351,124 (pp. 1-12). [cited by applicant]
Office Action dated Jun. 15, 2022 for U.S. Appl. No. 17/190,268 (pp. 1-17). [cited by applicant]
Giegerich, et al., “Automated Classification of “Bad Images” by Means of Machine Learning for Improvied Analysis of Vehicle Undercarriages,” TechConnect Briefs 2022, pp. 1-4. [cited by applicant]
Green, et al., “Vehicle Underscarriage Scanning for use in Crash Reconstruction,” FARO White Paper, 2015, 5 pages. [cited by applicant]
IVUS Intelligent Vehicle Undercarriage Scanner Brochusre, GatekeeperSecurity.com, 2 pages. [cited by applicant]
Kiong, Frederick Chong Chuen, “Vehicle Undercarriage Scanning System,” A disseration for ENG 4111 and ENG 4112 Research Project, University of Southern Queensland (USQ), Oct. 27, 2005, 163 pages. [cited by applicant]
Office Action (Final Rejection) dated Aug. 31, 2022 for U.S. Appl. No. 17/144,879 (pp. 1-14). [cited by applicant]
Office Action (Final Rejection) dated Nov. 14, 2022 for U.S. Appl. No. 16/861,097 (pp. 1-19). [cited by applicant]
Office Action (Final Rejection) dated Nov. 14, 2022 for U.S. Appl. No. 16/861,100 (pp. 1-19). [cited by applicant]
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Sep. 19, 2022 for U.S. Appl. No. 17/144,885 (pp. 1-7). [cited by applicant]
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Nov. 15, 2022 for U.S. Appl. No. 17/190,268 (pp. 1-7). [cited by applicant]
Extended European Search Report issued in App. No. EP20744281.5, dated Aug. 12, 2022, 7 pages. [cited by applicant]
Office Action (Final Rejection) dated Aug. 12, 2022 for U.S. Appl. No. 16/518,501 (pp. 1-21). [cited by applicant]
Office Action (Final Rejection) dated Aug. 12, 2022 for U.S. Appl. No. 16/518,558 (pp. 1-18). [cited by applicant]
Office Action (Non-Final Rejection) dated Aug. 18, 2022 for U.S. Appl. No. 17/174,250 (pp. 1-17). [cited by applicant]
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Aug. 17, 2022 for U.S. Appl. No. 16/692,219 (pp. 1-7). [cited by applicant]