A highly efficient block-based dynamic background model
David Russell, Shaogang Gong · 2006
A block-based dynamic background modelling technique featuring incremental update is presented, with the aim of increasing the sensitivity of background detection by considering the local connectivity of pixels. An accumulative model is maintained on-line by a heuristic algorithm to build up a statistical representation of a dynamic scene from a fixed camera view for foreground-background segmentation. The model is compared with a block-based technique employing cooccurrence [M. Seki et al., June 2003], and shown to be favourable in terms of both performance and conceptual simplicity. Using predominantly simple integer operations, the algorithm is highly amenable to direct implementation in hardware.