TY  - JOUR
AU  - Thierry Brouard
AU  - Jordi Gonzalez
AU  - Caifeng Shan
AU  - Massimo Piccardi
AU  - Larry S. Davis
PY  - 2014//
TI  - Special issue on background modeling for foreground detection in real-world dynamic scenes
T2  - MVAP
JO  - Machine Vision and Applications
SP  - 1101
EP  - 1103
VL  - 25
IS  - 5
PB  - Springer Berlin Heidelberg
N2  - Although background modeling and foreground detection are not mandatory steps for computer vision applications, they may prove useful as they separate the primal objects usually called “foreground” from the remaining part of the scene called “background”, and permits different algorithmic treatment in the video processing field such as video surveillance, optical motion capture, multimedia applications, teleconferencing and human–computer interfaces. Conventional background modeling methods exploit the temporal variation of each pixel to model the background, and the foreground detection is made using change detection. The last decade witnessed very significant publications on background modeling but recently new applications in which background is not static, such as recordings taken from mobile devices or Internet videos, need new developments to detect robustly moving objects in challenging environments. Thus, effective methods for robustness to deal both with dynamic backgrounds, i
SN  - 0932-8092
L1  - http://refbase.cvc.uab.es/files/BGS2014a.pdf
UR  - http://dx.doi.org/10.1007/s00138-013-0578-x
N1  - ISE; 600.078
ID  - Thierry Brouard2014
ER  -