Co-occurrence-based adaptive background model for robust object detection
Dong Liang, Shun’ichi Kaneko, Manabu Hashimoto, Kenji Iwatao, Xinyue Zhao, Yutaka Satoh · 2013
An illumination-invariant background model for detecting objects in dynamic scenes is proposed. It is robust in the cases of sudden illumination fluctuation as well as burst moving background. Unlike previous works, it distinguishes objects from a dynamic background using co-occurrence character between a target pixel and its supporting pixels in the form of multiple pixel pairs. Experiments used several challenging datasets that proved the robust performance of object detection in various environments.