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
Panoptes: scalable low-power video sensor networking technologies
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Improved Adaptive Gaussian Mixture Model for Background Subtraction
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Cyclops: in situ image sensing and interpretation in wireless sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
Proceedings of the 6th international conference on Information processing in sensor networks
Real-time foreground-background segmentation using codebook model
Real-Time Imaging
Consistent labeling of tracked objects in multiple cameras with overlapping fields of view
IEEE Transactions on Pattern Analysis and Machine Intelligence
A resource-aware distributed event space for pervasive smart camera networks
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
Cooperative object tracking and composite event detection with wireless embedded smart cameras
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
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Wireless embedded smart cameras not only capture images, but also can perform processing and communication. However,many system- and algorithm-wise challenges remain to be addressed to have operational, battery-powered wireless smart-camera networks, since they have limited processing power, memory, energy and bandwidth. In this paper, we present a wireless, embedded smart camera system for cooperative object tracking and event detection, wherein each camera platform consists of a camera board and a wireless mote. Light-weight background subtraction and tracking algorithms are implemented and run on the camera boards. Cameras communicate in a peer-to-peer manner over wireless links to exchange data, and thus to consistently track objects. In a wireless smart camera system, transferring large amounts of data between cameras should be avoided, since it requires more power, and incurs more communication delay. In the presented system, cameras exchange small-size packets for communication. Also, with wireless smart cameras, it is not viable to transfer all the captured frames to a base station due to limited resources. Instead, we define events of interest beforehand, and embedded smart cameras save only those portions of the live video capture where the defined event scenario occurs. We present results of tracking and detecting objects entering a region of interest, all of which are performed on the microprocessor of camera boards. We also show examples of consistently tracking objects, moving across different camera views, by wireless data exchange.