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Authors: Narayanan Chatapuram Krishnan ; Baoxin Li and Sethuraman Panchanathan

Affiliation: Center for Cognitive and Ubiquitous Computing, Arizona State University, United States

Keyword(s): Human Detection, graph cut, shape context, SVM.

Abstract: Detecting and estimating the presence and pose of a person in an image is a challenging problem. Literature has dealt with this as two separate problems. In this paper, we propose a system that introduces novel steps to segment the foreground object from the back ground and classifies the pose of the detected human as frontal, profile or back view. We use this as a front end to an intelligent environment we are developing to assist individuals who are blind in office spaces. The traditional background subtraction often results in silhouettes that are discontinuous, containing holes. We have incorporated the graph cut algorithm on top of background subtraction result and have observed a significant improvement in the performance of segmentation yielding continuous silhouettes without any holes. We then extract shape context features from the silhouette for training a classifier to distinguish between profile and nonprofile(frontal or back) views. Our system has shown promising results by achieving an accuracy of 87.5% for classifying profile and non profile views using an SVM on the real data sets that we have collected for our experiments. (More)

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Paper citation in several formats:
Chatapuram Krishnan, N.; Li, B. and Panchanathan, S. (2007). DETECTING AND CLASSIFYING FRONTAL, BACK AND PROFILE VIEWS OF HUMANS. In Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP; ISBN 978-972-8865-74-0; ISSN 2184-4321, SciTePress, pages 137-142. DOI: 10.5220/0002053101370142

@conference{visapp07,
author={Narayanan {Chatapuram Krishnan}. and Baoxin Li. and Sethuraman Panchanathan.},
title={DETECTING AND CLASSIFYING FRONTAL, BACK AND PROFILE VIEWS OF HUMANS},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP},
year={2007},
pages={137-142},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002053101370142},
isbn={978-972-8865-74-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP
TI - DETECTING AND CLASSIFYING FRONTAL, BACK AND PROFILE VIEWS OF HUMANS
SN - 978-972-8865-74-0
IS - 2184-4321
AU - Chatapuram Krishnan, N.
AU - Li, B.
AU - Panchanathan, S.
PY - 2007
SP - 137
EP - 142
DO - 10.5220/0002053101370142
PB - SciTePress

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