Multi-source human identification
Name
53827351-MIT.pdf
Description
Full printable version
Size
5.81 MB
Format
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Checksum (MD5)
9a1109314b0f22ea27f73e3016cececf
Author(s)
Kim, Brian A. (Brian Andrew), 1979-
Advisor(s)
Tomaso Poggio.
Date Issued
2003
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, a multi-source system for human identification is developed. The system uses three sources: face classifier, height classifier, and color classifier. In the process of developing this system, classifier combination and the integration of classifer outputs over sequences of data points were studied in detail. The method of classifier combination used relies on weighing classifiers based on the Maximum Likelihood estimation of class probabilities. The integration of classifer outputs, which is termed "temporal integration" in this thesis, has been developed to take advantage of the information implicitly contained in data correlated through time. In all experiments performed, temporal integration has improved classification, up to 40% in some cases. Meanwhile, the method of temporally integrating the outputs of multiple classifiers fused using our classifier weighting method outperforms all individual classifiers in the system.
Description
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.
Includes bibliographical references (p. 59-60).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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