PT Journal
AU Thierry Brouard
   Jordi Gonzalez
   Caifeng Shan
   Massimo Piccardi
   Larry S. Davis
TI Special issue on background modeling for foreground detection in real-world dynamic scenes
SO Machine Vision and Applications
JI MVAP
PY 2014
BP 1101
EP 1103
VL 25
IS 5
DI 10.1007/s00138-013-0578-x
AB 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
ER