System and method for vehicle detection and tracking
First Claim
Patent Images
1. A method for detecting one or more objects belonging to the same object class comprising the steps of:
- a) receiving a video sequence from a video camera comprised of a plurality of image frames;
b) applying one or more component classifiers to detect components of objects in an image frame in the video sequence, wherein the component classifiers include classifiers for detecting object components of different sizes at multiple scales;
c) computing a confidence score based in part on the response from the one or more component detectors;
d) repeating steps b) and c) to detect components of objects belonging to the same object class in additional images frames in the video sequence; and
e) accumulating confidence scores from the component detectors to determine if an object is detected,wherein said method is adapted for detecting moving and stationary objects from a moving video camera.
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Abstract
A system and method for detecting and tracking an object is disclosed. A camera captures a video sequence comprised of a plurality of image frames. A processor receives the video sequence and analyzes each image frame to determine if an object is detected. The processor applies one or more classifiers to an object in each image frame and computes a confidence score based on the application of the one or more classifiers to the object. A database stores the one or more classifiers and vehicle training samples. A display displays the video sequence.
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Citations
93 Claims
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1. A method for detecting one or more objects belonging to the same object class comprising the steps of:
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a) receiving a video sequence from a video camera comprised of a plurality of image frames; b) applying one or more component classifiers to detect components of objects in an image frame in the video sequence, wherein the component classifiers include classifiers for detecting object components of different sizes at multiple scales; c) computing a confidence score based in part on the response from the one or more component detectors; d) repeating steps b) and c) to detect components of objects belonging to the same object class in additional images frames in the video sequence; and e) accumulating confidence scores from the component detectors to determine if an object is detected, wherein said method is adapted for detecting moving and stationary objects from a moving video camera. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47)
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48. A system for detection and tracking an object comprising:
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a camera for capturing a video sequence comprised of a plurality of image frames; a processor for receiving the video sequence and analyzing each image frame to determine if an object is detected, said processor applying one or more component classifiers to detect components of objects in each image frame and computing a confidence score based on the response from the one or more component detectors and the result of additional validation, wherein the accumulated confidence scores is inferred from confidence scores across multiple frames using a recursive filter; and a database for storing the one or more classifiers and object training samples, wherein said system is adapted for detecting moving and stationary objects from a moving video camera. - View Dependent Claims (49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92)
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93. A method for detecting one or more objects belonging to the same object class comprising the steps of:
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a) receiving a video sequence from a video camera comprised of a plurality of image frames; b) applying one or more component classifiers to detect components of objects in an image frame in the video sequence, wherein the one or more component classifiers include overlapping component classifiers, and wherein component classifiers are defined by discriminant features and decision rules which are learned through boosting; c) computing a confidence score based in part on the response from the one or more component detectors; d) repeating steps b) and c) to detect components of objects belonging to the same object class in additional images frames in the video sequence; and e) accumulating confidence scores from the component detectors to determine if an object is detected, wherein said method is adapted for detecting moving and stationary objects from a moving video camera.
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Specification