TY - GEN
T1 - Background updating with the use of intrinsic curves
AU - Salas, Joaquín
AU - Martínez, Pedro
AU - González, Jordi
PY - 2006
Y1 - 2006
N2 - A primary tool to extract information about moving objects is back-ground 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.
AB - A primary tool to extract information about moving objects is back-ground 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.
UR - http://www.scopus.com/inward/record.url?scp=33749655429&partnerID=8YFLogxK
U2 - 10.1007/11867586_67
DO - 10.1007/11867586_67
M3 - Contribución a la conferencia
SN - 3540448918
SN - 9783540448914
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 731
EP - 742
BT - Image Analysis and Recognition - Third International Conference, ICIAR 2006, Proceedings
PB - Springer Verlag
T2 - 3rd International Conference on Image Analysis and Recognition, ICIAR 2006
Y2 - 18 September 2006 through 20 September 2006
ER -