RoboCup: The Robot World Cup Initiative
AGENTS '97 Proceedings of the first international conference on Autonomous agents
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Pedestrian Detection in Crowded Scenes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
PCA-SIFT: a more distinctive representation for local image descriptors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Automatic target recognition by matching oriented edge pixels
IEEE Transactions on Image Processing
A survey of techniques for human detection in static images
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
A feature compression scheme for large scale image retrieval systems
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
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In this paper, we address the problem of identifying and localizing multiple instances of highly deformable objects in real-time video data. We present an approach which uses PCA-SIFT (Scale Invariant Feature Transform) in combination with a clustered voting scheme to achieve detection and localization of multiple objects while providing robustness against rapid shape deformation, partial occlusion, and perspective changes. We test our approach in two highly deformable robot domains and evaluate Its performance using ROC (Receiver Operating Characteristic) statistics.