Soft competitive adaptation: neural network learning algorithms based on fitting statistical mixtures
Performance of optical flow techniques
International Journal of Computer Vision
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Patterns of Activity Using Real-Time Tracking
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 Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Framework for High-Level Feedback to Adaptive, Per-Pixel, Mixture-of-Gaussian Background Models
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
A master-slave system to acquire biometric imagery of humans at distance
IWVS '03 First ACM SIGMM international workshop on Video surveillance
Effective Gaussian Mixture Learning for Video Background Subtraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Modeling of Dynamic Scenes for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Novel region-based modeling for human detection within highly dynamic aquatic environment
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Image segmentation in video sequences: a probabilistic approach
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
A survey on visual surveillance of object motion and behaviors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Detecting moving objects, ghosts, and shadows in video streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Over a decade ago, simply recording a few minutes of CCTV footage required special hardware. Today, with the emergence of new sensors and improved processing hardware, a relatively inexpensive personal computer can process and store video in real-time, which fundamentally enables our research. Automated visual surveillance is poised to be a key technology in the fight against crime, particularly in monitoring security sensitive areas. A significant advantage of this technology lies in its non-intrusive nature in multi-target tracking. In this paper, we present an automated attention mechanism that allows for the operation of vision-based surveillance systems in a wide variety of environments typical of general indoor/outdoor settings. Different applications of our system are demonstrated including real-time abandoned luggage detection and general outdoor person/vehicle classification.