Invention Grant
- Patent Title: Surveillance system using deep network flow for multi-object tracking
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Application No.: US15695625Application Date: 2017-09-05
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Publication No.: US10402983B2Publication Date: 2019-09-03
- Inventor: Samuel Schulter , Wongun Choi , Paul Vernaza , Manmohan Chandraker
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: JP
- Assignee: NEC Corporation
- Current Assignee: NEC Corporation
- Current Assignee Address: JP
- Agent Joseph Kolodka
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06T7/20 ; G06T7/77 ; G06T7/70 ; H04N7/18 ; G06K9/62

Abstract:
A surveillance system and method are provided. The surveillance system includes at least one camera configured to capture a set of images of a given target area that includes a set of objects to be tracked. The surveillance system includes a memory storing a learning model configured to perform multi-object tracking by jointly learning arbitrarily parameterized and differentiable cost functions for all variables in a linear program that associates object detections with bounding boxes to form trajectories. The surveillance system includes a processor configured to perform surveillance of the target area to (i) detect the objects and track locations of the objects by applying the learning model to the images in a surveillance task that uses the multi-object tracking, and (ii), provide a listing of the objects and their locations for surveillance task. A bi-level optimization is used to minimize a loss defined on a solution of the linear program.
Public/Granted literature
- US20180130216A1 SURVEILLANCE SYSTEM USING DEEP NETWORK FLOW FOR MULTI-OBJECT TRACKING Public/Granted day:2018-05-10
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