Object Matching Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable Shape Detection and Description via Model-Based Region Grouping
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer and Robot Vision
Multiple video object tracking in complex scenes
Proceedings of the tenth ACM international conference on Multimedia
Second order image statistics in computer graphics
APGV '04 Proceedings of the 1st Symposium on Applied perception in graphics and visualization
Statistical modeling of complex backgrounds for foreground object detection
IEEE Transactions on Image Processing
Object detection and tracking for night surveillance based on salient contrast analysis
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Vs-star: A visual interpretation system for visual surveillance
Pattern Recognition Letters
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Moving object detection is a challenging task for night security because of bad video quality. In this paper, we propose a robust real time objects detection method for night visual surveillance based on human visual system. By measuring contrast information variation in multiple successive frames, a spatio-temporal contrast change image (CCI) is formed. Then the multi-frame correspondence technology is employed to robustly extract salient motions or moving objects from CCI. Since CCI is a statistical measurement of variation based on human visual system, the proposed method is effective at night and better than traditional detection methods. Experiments on real scene show that the method based on contrast feature is effective for night object detection and tracking, our approach is also robust to camera scale variation as well as low computation cost.