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https://hdl.handle.net/2440/64730
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Type: | Conference paper |
Title: | A novel shape feature for fast region-based pedestrian recognition |
Author: | Shahrokni, Ali Gawley, Darren John Ferryman, J. |
Citation: | Proceedings, 2010 20th International Conference on Pattern Recognition (ICPR 2010), 2010; pp.444-447 |
Publisher: | IEEE |
Issue Date: | 2010 |
ISBN: | 9780769541099 |
Conference Name: | International Conference on Pattern Recognition (20th : 2010 : Istanbul, Turkey) ICPR 2010 |
School/Discipline: | School of Computer Science |
Statement of Responsibility: | Ali Shahrokni, Darren Gawley, James Ferryman |
Abstract: | A new class of shape features for region classification and high-level recognition is introduced. The novel Randomised Region Ray (RRR) features can be used to train binary decision trees for object category classification using an abstract representation of the scene. In particular we address the problem of human detection using an over segmented input image. We therefore do not rely on pixel values for training, instead we design and train specialised classifiers on the sparse set of semantic regions which compose the image. Thanks to the abstract nature of the input, the trained classifier has the potential to be fast and applicable to extreme imagery conditions. We demonstrate and evaluate its performance in people detection using a pedestrian dataset. |
Rights: | © 2010 IEEE |
DOI: | 10.1109/ICPR.2010.117 |
Appears in Collections: | Computer Science publications |
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