IP Library › Granted Patent US 12,493,966
Granted Patent B2
US 12,493,966 · App. 18/088,094 · Granted Dec 9, 2025

Aligned time surfaces via dense optical flows for event-based object detection, identification and tracking

Inventors: Ganesh Sundaramoorthi (Belmont, MA); Kin Gwn Lore (Belmont, MA)
Assignee: Raytheon Company
G06T7/20G06T3/18G06T5/73
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Quick Facts
Patent No.
US 12,493,966
App. No.
18/088,094
Granted
Dec 9, 2025
Kind
B2
Abstract

Systems and methods are provided for producing aligned and aggregated aligned time surfaces. An exemplary method includes: receiving camera event data from a first location; computing, using the camera event data, a plurality of unaligned time surfaces; determining a plurality of optical flows corresponding to the unaligned time surfaces; determining, using the optical flows, an accumulated optical flow for mapping displacement between any two time periods; producing, using the optical flows, for a plurality of consecutive mapped time surfaces; performing, using the accumulated optical flow, warping of the mapped time surfaces producing corresponding aligned time surfaces; and aggregating the aligned time surfaces to produce an image having lowered blurring of object boundaries.

Claims (42)

1 . A system for producing aligned time surfaces, the system comprising one or more computing device processors; and

one or more computing device memories, coupled to the one or more computing device processors, the one or more computing device memories storing instructions executed by the one or more computing device processors, wherein the instructions are configured to:

receive camera event data from a first location;

compute, using the camera event data, a plurality of unaligned time surfaces;

determine a plurality of optical flows corresponding to the unaligned time surfaces;

determine, using the optical flows, corresponding displacement parameters by respectively combining (a) a location to be mapped and (b) a result of using an integral on an optical flow of the optical flows for mapping displacement between any two time periods;

produce, using the displacement parameters, a plurality of consecutive mapped time surfaces;

perform warping, using the optical flows, of the mapped time surfaces producing corresponding aligned time surfaces; and

aggregate the aligned time surfaces to produce an image having lowered blurring of object boundaries.

2 . The system of claim 1 , wherein the first location is an event camera system.

3 . The system of claim 1 , wherein the first location is a remote storage device for storing the camera event data.

4 . The system of claim 1 , wherein while computing the unaligned time surfaces, the instructions are configured to aggregate the unaligned time surfaces in accordance with time and space.

5 . The system of claim 1 , wherein the unaligned time surfaces comprise information of at least one moving object.

6 . The system of claim 1 , wherein while determining the plurality of optical flows, the instructions are configured to determine a velocity of at least one moving object in the unaligned time surfaces.

7 . The system of claim 1 , wherein while performing warping of the unaligned time surfaces, the instructions are configured to align, using an accumulated optical flow, the aligned time surfaces in accordance with time and space.

8 . The system of claim 1 , wherein the instructions further configured to send the image downstream to an object identification, detection, and/or tracking process.

9 . The system of claim 8 , wherein while sending the image downstream, the instructions are configured to execute the object identification, detection, and/or tracking process on a remote system.

10 . A method for producing aligned time surfaces, the method comprising:

receiving camera event data from a first location;

computing, using the camera event data, a plurality of unaligned time surfaces;

determining a plurality of optical flows corresponding to the unaligned time surfaces;

determining, using the optical flows, corresponding displacement parameters by respectively combining (a) a location to be mapped and (b) a result of using an integral on an optical flow of the optical flows for mapping displacement between any two time periods;

producing, using the displacement parameters, a plurality of consecutive mapped time surfaces;

performing, using the optical flows, warping of the mapped time surfaces producing corresponding aligned time surfaces; and

aggregating the aligned time surfaces to produce an image having lowered blurring of object boundaries.

11 . The method of claim 10 , wherein the first location is an event camera system.

12 . The method of claim 10 , wherein the first location is a remote storage device for storing the camera event data.

13 . The method of claim 10 , wherein the computing the unaligned time surfaces comprises aggregating the unaligned time surfaces in accordance with time and space.

14 . The method of claim 10 , wherein the unaligned time surfaces comprise information of at least one moving object.

15 . The method of claim 10 , wherein determining the plurality of optical flows comprises determining a velocity of at least one moving object in the unaligned time surfaces.

16 . The method of claim 15 , wherein an accumulated optical flow comprises accumulated information associated with processing of the optical flows.

17 . The method of claim 16 , wherein performing warping of the unaligned time surfaces comprises aligning, using the accumulated optical flow, the aligned time surfaces in accordance with time and space.

18 . The method of claim 10 further comprising sending the image downstream to an object identification, detection, and/or tracking process.

19 . The method of claim 18 , wherein sending the image downstream comprises executing the object identification, detection, and/or tracking process on a remote system.

20 . A non-transitory computer-readable storage medium storing instructions which when executed by a computer cause the computer to perform a method for producing aligned time surfaces, the method comprising:

receiving camera event data from a first location;

computing, using the camera event data, a plurality of unaligned time surfaces;

determining a plurality of optical flows corresponding to the unaligned time surfaces;

determining, using the optical flows, corresponding displacement parameters by respectively combining (a) a location to be mapped and (b) a result of using an integral on an optical flow of the optical flows for mapping displacement between any two time periods;

producing, using the displacement parameters, a plurality of consecutive mapped time surfaces;

performing warping, using the optical flows, of the mapped time surfaces producing corresponding aligned time surfaces; and

aggregating the aligned time surfaces to produce an image having lowered blurring of object boundaries.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 13, 2023
From: SUNDARAMOORTHI, GANESH; LORE, KIN GWN
To: RAYTHEON TECHNOLOGIES CORPORATION
Reel/Frame 062674/0108 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 13, 2023
From: RAYTHEON TECHNOLOGIES CORPORATION
To: RAYTHEON COMPANY
Reel/Frame 062676/0689 →
Continuity (1)
Related Publication 20240212166A1 · Jun 27, 2024
References Cited (14)
US 11290682B1 · Shaburov · 2022 [cited by examiner]
US 20160330374A1 · Ilic · 2016 [cited by examiner]
US 20230216999A1 · Zobel · 2023 [cited by examiner]
US 20230267624A1 · Konda · 2023 [cited by examiner]
CN 116703965A · 2023 [cited by examiner]
Nagata, Jun, et al. “Optical Flow Estimation by Matching Time Surface with Event-Based Cameras”; Sensors, vol. 21, No. 4, Feb. 6, 2021, p. 1150, https://doi.org/10.3390/s21041150. Accessed Mar. 26, 2025. (Year: 2021). [cited by examiner]
Beauchemin, S. S., & Barron, J. L. (1995). The computation of optical flow. ACM Computing Surveys, 27(3), 433-466. https://doi.org/10.1145/212094.212141 (Year: 1995). [cited by examiner]
“International Application Serial No. PCT/US2023/078356, International Search Report mailed Mar. 11, 2024”, 3 pgs. [cited by applicant]
“International Application Serial No. PCT/US2023/078356, Written Opinion mailed Mar. 11, 2024”, 8 pgs. [cited by applicant]
Gallego, Guillermo, et al., “Event-based Vision: A Survey”, Computer Science, Medicine IEEE transactions of pattern analysis and machine intelligence, (2020), 30 pgs. [cited by applicant]
Guillermo, Gallego, et al., “A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation”, arxiv.org, Cornell University Library, 201 Olin Library Cornel… [cited by applicant]
Lagorce, Xavier, et al., “HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Computer Society, USA vol. 39, No. 7, (Jul. 1, 2017… [cited by applicant]
Wu, Yilun, et al., “Lightweight Event-based Optical Flow Estimation via Iterative Deblurring”, [Online]. Retrieved from the Internet: <https://export.arxiv.org/abs/2211.13726v1>, (Nov. 24, 2022), 9 pgs. [cited by applicant]
Zhu, Alex Zihao, et al., “Unsupervised Event-Based Learning of Optical Flow, Depth, and Egomotion”, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, (Jun. 15, 2019), 989-997. [cited by applicant]