Live Video Segmentation in Dynamic Backgrounds Using Thermal Vision

In this paper we describe a new technique for live video segmentation of human regions from dynamic backgrounds. Correct segmentations are produced in real-time even in severe background changes caused by camera movement and illumination changes. There are three key contributions. The first contribution is the employing of the thermal cue which proves to be very effective when fused with color. Second, we propose a new speed-up GraphCut algorithm by combining with the Bayesian estimation. The third contribution is a novel online learning method using accumulative histograms. The segmentation accuracy and speed are quite capable of the live video segmentation purpose.