Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Efficient Visual Event Detection Using Volumetric Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
A Roadmap to the Integration of Early Visual Modules
International Journal of Computer Vision
Sharing Visual Features for Multiclass and Multiview Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vision-based human motion analysis: An overview
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words
International Journal of Computer Vision
Boosting with temporal consistent learners: an application to human activity recognition
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
Extracting motion features for visual human activity representation
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
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We present a method to detect people waving using video streams from a fixed camera system. Waving is a natural means of calling for attention and can be used by citizens to signal emergency events or abnormal situations in future automated surveillance systems. Our method is based on training a supervised classifier using a temporal boosting method based on optical flow-derived features. The base algorithm shows a low false positive rate and if further improves through the definition of a minimum time for the duration of the waving event. The classifier generalizes well to scenarios very different from where it was trained. We show that a system trained indoors with high resolution and frontal postures can operate successfully, in real-time, in an outdoor scenario with large scale differences and arbitrary postures.