Biologically Inspired Particle Filter for Robust Visual Tracking

Although particle filter and its variants like KPF and UPF achieve great success in many visual tracking applications, they depend on local proposal distributions and hence always fall flat in cases of global object shift and large-scale object movement. To address this issue, we present the concept of global proposal distribution for particle filter with the inspiration from biological vision examples and term their combination as biologically inspired particle filter (BI-PF). Three types of global proposal distributions are proposed based on biological vision inspired saliency maps, including motion, color, and contrast saliency map. In order for BI-PF to mimic the way human’s eye tracks object, local and global proposal distribution are dynamically integrated through a threshold determining when to switch between them. Experimental results demonstrate the outperformance of our BI-PFs over particle filter, KPF, and UPF. Keywards: Visual Tracking, Particle Filter, Proposal Distribution, Biological Vision, Saliency Map