Motion analysis with application to assistive vision technology

Abstract

The analysis of motion in image sequences represents a popular and constantly growing research field. In This work a motion analysis scheme is proposed to function as an assistive vision technology tool. The first stage of this methodology includes a video stabilization scheme as a preprocessing stage. In the next stage a nonlinear spatio-temporal diffusion approach is applied and a kernel based density estimation method follows to assess the motion activity. This overall process is completed by watershed-based segmentation to detect the moving areas. The presented experimental results indicate the efficiency of this scheme in detecting and segmenting the moving areas.