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Abstract: In this paper we present a component based person detection system that is capable of detecting frontal, rear and near side views of people, and partially occluded persons in cluttered scenes. The framework that is described here for people is easily applied to other objects as well. The motivation for developing a component based approach is two fold: first, to enhance the performance of person detection systems on frontal and rear views of people and second, to develop a framework that... (Update)
Context of citations to this paper: More
.... approaches either rely on low level [1] or common generic parts [2] or require parts to be manually de ned and separated [6] (or both) We believe that the expressivity of a part based representation can be enhanced by considering distinctive, higher level parts...
...views to check for part matches. Filter sets appropriated for this purpose include convolutional kernels like Gabor wavelets [2] [13][18] and Gaussian derivatives[18] 2] 17] differential invariants based on combining the outputs of those kernels [19] local eigenspaces...
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BibTeX entry: (Update)
A. Mohan. Object detection in images by components. A.I. Memo 1664, Center for Biological and Computational Learning, M.I.T., Cambridge, MA, 1999. http://citeseer.ist.psu.edu/mohan99object.html More
@techreport{ mohan99object,
author = "Anuj Mohan",
title = "Object Detection in Images by Components",
number = "AIM-1664",
year = "1999",
url = "citeseer.ist.psu.edu/mohan99object.html" }
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