2026-09-20T19:00:42Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/284432022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Tomaso Poggio.
Leung, Brian, 1981-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2005-09-26T20:29:54Z
2005-09-26T20:29:54Z
2004
2004
http://hdl.handle.net/1721.1/28443
57015536
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (p. 67-71).
Recent studies in object detection have shown that a component-based approach is more resilient to partial occlusions of objects, and more robust to natural pose variations, than the traditional global holistic approach. In this thesis, we consider the task of building a component-based detector in a more difficult domain: cars in natural images of street scenes. We demonstrate reasonable results for two different component-based systems, despite the large inherent variability of cars in these scenes. First, we present a car classification scheme based on learning similarities to features extracted by an interest operator. We then compare this system to traditional global approaches that use Support Vector Machines (SVMs). Finally, we present the design and implementation of a system to locate cars based on the detections of human-specified components.
by Brian Leung.
M.Eng.
71 p.
3329317 bytes
3336431 bytes
application/pdf
application/pdf
en_US
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Component-based car detection in street scene images
Thesis
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