Stereo Matching as a Nearest-Neighbor Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation and Representing Background in Color Images
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
A Background Layer Model for Object Tracking Through Occlusion
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Detecting moving objects, ghosts, and shadows in video streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayes decision test for detecting uncovered-background and moving pixels in image sequences
IEEE Transactions on Image Processing
Efficient moving object segmentation algorithm using background registration technique
IEEE Transactions on Circuits and Systems for Video Technology
Toward visually inferring the underlying causal mechanism in a traffic-light-controlled crossroads
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
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A primary tool to extract information about moving objects is background subtraction. In this technique, the difference between a model of what is static, or background, and the current image of the scene gives information about what is in the prime plane or foreground. This study focus on the pixelwise updating mechanism of the background model throughout the analysis of the images provided by a fixed camera. The concept of intrinsic curves, early introduced in the field of stereovision, is extrapolated to the problem of detecting the moving boundaries. We use a mixture of Gaussians to register information about the recent history of the pixel dynamics. Our method improves this model in two ways. Firstly, it reduces the chances of feeding the mixture of Gaussians with foreground pixels. Secondly, it takes into account not just the scalar pixel value but a richer description of the pixel’s dynamics that carries information about the interpixel variation. Ample experimental results in a wide range of environments, including indoors, outdoors, for a different set of illumination conditions both natural and artificial are shown.