A novel shape feature for fast region-based pedestrian recognition
Shahrokni, A., Gawley, D. and Ferryman, J. M. (2010) A novel shape feature for fast region-based pedestrian recognition. In: Proceedings 20th International Conference on Pattern Recognition. IEEE Computer Society Press, pp. 444-447. ISBN 9780769541099
Full text not archived in this repository.
To link to this article DOI: 10.1109/ICPR.2010.117
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.