A Random Field Model for Improved Feature Extraction and Tracking

This paper presents a novel method for illuminationinvariant and contrast preserving feature extraction, aimed at improving performance of tracking under complex light condition. Features to be extracted are represented as a weight field. An energy function of the field is defined as an approximate variance in robust statistics. A simple nonlinear iterative rule is derived to compute the optimal field. The optimal field is shown to be invariant to global illumination switching, and preserving target/background contrast. We incorporate the feature extraction method into a mean-shift tracker and this achieves reliable results on realworld sequences in complex scenes and varying illumination.

• Type: Conference
• Year: 2006
• Where: AVSS
• Authors: Xiaotong Yuan, Stan Z. Li
• Keywords: AVSS 2006, Contrast Preserving Feature, Feature Extraction, Optimal field, Signal Processing