Robust Real-Time Periodic Motion Detection, Analysis, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Trainable System for Object Detection
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pedestrian Detection Using Wavelet Templates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Moving Target Classification and Tracking from Real-time Video
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Automated Detection of Human for Visual Surveillance System
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Stereo- and neural network-based pedestrian detection
IEEE Transactions on Intelligent Transportation Systems
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People detection in outdoor environments is one of the most important problems in the context of video surveillance. In this work we propose an example-based learning technique to detect people in dynamic scenes. A classification based on people shape and not on image content has been applied. First, motion information and background subtraction have been used for highlighting objects of interest, then geometric and statistical information have been extracted from horizontal and vertical projections of detected objects to represent people shape. Finally, a supervised three layer neural network has been used to properly classify objects. Experiments have been performed on real image sequences acquired in a parking area. The results have shown that the proposed method is robust, reliable, fast and it can be easily adapted for the detection of any other moving object in the scene.