Method and apparatus for joint kinematic and feature tracking using probabilistic argumentation
First Claim
1. A method for joint kinematic and feature tracking comprising acts of:
- receiving kinematic measurements and feature/class measurements regarding an object from at least one sensor;
performing a probabilistic argumentation operation on the feature/class measurements using information from a rule-based knowledge base and a track file regarding the object to generate feature track likelihood scores that provide information regarding likely tracks for the object;
generating kinematic track likelihood scores based on the kinematic measurements and the track file regarding the object;
generating joint track likelihood scores based on the feature track likelihood scores and the kinematic track likelihood scores;
using the joint track likelihood scores to generate a multi-frame track measurement association to determine a most likely track for the object; and
updating the track file with the most likely track for the object;
whereby the method tracks an object and continually updates the track file for the object, so that the most likely trajectory of the object is obtained.
1 Assignment
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Accused Products
Abstract
A method, apparatus, and computer program product for joint kinematic and feature tracking are presented. Kinematic measurements and feature/class measurements regarding an object are received from a sensor. A probabilistic argumentation operation is performed on the feature/class measurements using information from a knowledge base and a track file ect to generate feature track likelihood scores regarding likely tracks for the object. Kinematic track likelihood scores are generated based on the kinematic measurements and the track file. Joint track likelihood scores are generated based on the feature track likelihood scores and the kinematic track likelihood scores. Joint track likelihood scores are used to generate a multi-frame track measurement association to determine a most likely track for the object. The track file is continually updated with the most likely track for the object, so that the most likely trajectory of the object is obtained.
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Citations
48 Claims
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1. A method for joint kinematic and feature tracking comprising acts of:
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receiving kinematic measurements and feature/class measurements regarding an object from at least one sensor;
performing a probabilistic argumentation operation on the feature/class measurements using information from a rule-based knowledge base and a track file regarding the object to generate feature track likelihood scores that provide information regarding likely tracks for the object;
generating kinematic track likelihood scores based on the kinematic measurements and the track file regarding the object;
generating joint track likelihood scores based on the feature track likelihood scores and the kinematic track likelihood scores;
using the joint track likelihood scores to generate a multi-frame track measurement association to determine a most likely track for the object; and
updating the track file with the most likely track for the object;
whereby the method tracks an object and continually updates the track file for the object, so that the most likely trajectory of the object is obtained. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A computer program product for joint kinematic and feature tracking comprising a computer-readable medium having computer-executable instructions encoded therein for causing a computer to perform operations of:
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receiving kinematic measurements and feature/class measurements regarding an object from at least one sensor;
performing a probabilistic argumentation operation on the feature/class measurements using information from a rule-based knowledge base and a track file regarding the object to generate feature track likelihood scores that provide information regarding likely tracks for the object;
generating kinematic track likelihood scores based on the kinematic measurements and the track file regarding the object;
generating joint track likelihood scores based on the feature track likelihood scores and the kinematic track likelihood scores;
using the joint track likelihood scores to generate a multi-frame track measurement association to determine a most likely track for the object; and
updating the track file with the most likely track for the object;
whereby the computer program product tracks an object and continually updates the track file for the object, so that the most likely trajectory of the object is obtained. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32)
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33. An apparatus for joint kinematic and feature tracking, the apparatus comprising a computer system, the computer system including:
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an input for receiving kinematic measurements and feature/class measurements regarding an object from at least one sensor;
a probabilistic argumentation module for performing a probabilistic argumentation operation on the feature/class measurements using information from a rule-based knowledge base and a track file regarding the object to generate feature track likelihood scores that provide information regarding likely tracks for the object;
a kinematic track likelihood score generator for generating kinematic track likelihood scores based on the kinematic measurements and the track file regarding the object;
a joint track likelihood score generator for generating joint track likelihood scores based on the feature track likelihood scores and the kinematic track likelihood scores;
a track measurement association generator for using the joint track likelihood scores to generate a multi-frame track measurement association to determine a most likely track for the object; and
a track file updating module for updating the track file with the most likely track for the object;
whereby the method tracks an object and continually updates the track file for the object, so that the most likely trajectory of the object is obtained. - View Dependent Claims (34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48)
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Specification