System and method for vehicle detection and tracking
First Claim
Patent Images
1. A method for vehicle detection and tracking, comprising:
- acquiring video data including a plurality of frames;
comparing a first frame of the acquired video data against a set of one or more vehicle detectors to form vehicle hypotheses;
pruning and verifying the vehicle hypotheses using a set of coarse-to-fine constraints to detect a vehicle; and
tracking the detected vehicle within one or more subsequent frames of the acquired video data by fusing shape template matching with one or more vehicle detectors,wherein the set of coarse-to-fine constraints includes a first level in which an objective function is replaced by a course approximation and a second level in which mode locations obtained in the first level are refined by optimizing the objective function.
5 Assignments
0 Petitions
Accused Products
Abstract
A method for vehicle detection and tracking includes acquiring video data including a plurality of frames, comparing a first frame of the acquired video data against a set of one or more vehicle detectors to form vehicle hypotheses, pruning and verifying the vehicle hypotheses using a set of course-to-fine constraints to detect a vehicle, and tracking the detected vehicle within one or more subsequent frames of the acquired video data by fusing shape template matching with one or more vehicle detectors.
56 Citations
34 Claims
-
1. A method for vehicle detection and tracking, comprising:
-
acquiring video data including a plurality of frames; comparing a first frame of the acquired video data against a set of one or more vehicle detectors to form vehicle hypotheses; pruning and verifying the vehicle hypotheses using a set of coarse-to-fine constraints to detect a vehicle; and tracking the detected vehicle within one or more subsequent frames of the acquired video data by fusing shape template matching with one or more vehicle detectors, wherein the set of coarse-to-fine constraints includes a first level in which an objective function is replaced by a course approximation and a second level in which mode locations obtained in the first level are refined by optimizing the objective function.
-
-
2. A method for vehicle detection and tracking, comprising:
-
acquiring video data including a plurality of frames; comparing a first frame of the acquired video data against a set of one or more vehicle detectors to form vehicle hypotheses; pruning and verifying the vehicle hypotheses using a set of coarse-to-fine constraints to detect a vehicle; and tracking the detected vehicle within one or more subsequent frames of the acquired video data by fusing shape template matching with one or more vehicle detectors, wherein the detected vehicle is tracked within subsequent frames by kernel-based probabilistic shape tracker, and wherein the kernel-based probabilistic shape tracker estimates vehicle motion by matching feature points in an image region with one or more shape templates that have been extracted from a corresponding target of a previous frame. - View Dependent Claims (3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27)
-
-
9. A method for vehicle detection and tracking, comprising:
-
acquiring video data including a plurality of frames; comparing a first frame of the acquired video data against a set of one or more vehicle detectors to form vehicle hypotheses; pruning and verifying the vehicle hypotheses using a set of coarse-to-fine constraints to detect a vehicle; and tracking the detected vehicle within one or more subsequent frames of the acquired video data by fusing shape template matching with one or more vehicle detectors, wherein the set of coarse-to-fine constraints includes vehicle part detectors learned from examples of vehicle lower left part and vehicle lower right part, and wherein the vehicle part detectors are followed by an orientation histogram constraint. - View Dependent Claims (10)
-
-
28. A system for vehicle detection and tracking, comprising:
-
a camera mounted on a moving host vehicle for acquiring video data including a plurality of frames; and a central tracker for comparing a first frame of the acquired video data against a set of one or more vehicle detectors to form a vehicle detection hypotheses, verifying the vehicle detection hypotheses to detect a vehicle, and tracking the detected vehicle within one or more subsequent frames of the acquired video data, wherein the detected vehicle is tracked within subsequent frames by kernel-based probabilistic shape tracker, and wherein the kernel-based probabilistic shape tracker estimates vehicle motion by matching feature points in an image region with one or more shape templates that have been extracted from a corresponding target of a previous frame. - View Dependent Claims (29, 30)
-
-
31. A computer system comprising:
-
a processor; and a program storage device readable by the computer system, embodying a program of instructions executable by the processor to perform method steps for vehicle detection and tracking, the method comprising; acquiring video data including a plurality of frames; comparing a first frame of the acquired video data against a set of one or more vehicle detectors to form a vehicle detection hypotheses; and tracking the detected vehicle within one or more subsequent frames of the acquired video data, wherein the detected vehicle is tracked within subsequent frames by kernel-based probabilistic shape tracker, and wherein the kernel-based probabilistic shape tracker estimates vehicle motion by matching feature points in an image region with one or more shape templates that have been extracted from a corresponding target of a previous frame. - View Dependent Claims (32, 33, 34)
-
Specification