Using robust audio and video processing technologies to alleviate the elderly cognitive decline
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Person tracking for ambient camera selection in complex sports environments
Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts
The AIT 2D Face Detection and Tracking System for CLEAR 2007
Multimodal Technologies for Perception of Humans
Where and Who? Person Tracking and Recognition System
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Proceedings of the 2nd International Conference on PErvasive Technologies Related to Assistive Environments
Audio-visual active speaker tracking in cluttered indoors environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
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This paper proposes a robust background estimator for fixed cameras, to be used for foreground segmentation in tracking systems. The estimator is based on a variation of Stauffer's dynamic background algorithm, where the background learning rate is spatiotemporally adapted. The adaptation is based on the position, size and velocity of the various foreground objects already detected. The evidence for the initialization and tracking of the foreground objects is obtained by combining a pixel map showing the temporal persistence of each image pixel and the edge binary image. The spatiotemporal adaptation of the learning rate overcomes the problem of fading immobile or slowly moving objects into the background encountered in all to-date variations of Stauffer's algorithm, while the combination with edge information allows for objects already present in the scene at startup time and new objects to be treated by the same image processing module.