Fuzzy chamfer distance and its probabilistic formulation for visual tracking

The paper presents a fuzzy chamfer distance and its probabilistic formulation for edge-based visual tracking. First, connections of the chamfer distance and the Hausdorff distance with fuzzy objective functions for fuzzy clustering are shown using a reformulation theorem. A fuzzy chamfer distance (FCD) based on fuzzy objective functions and a probabilistic formulation of the fuzzy chamfer distance (PFCD) based on data association methods are then presented, which can all be regarded as reformulated fuzzy objective functions and minimized with iterative algorithms. Results on challenging sequences demonstrate the performance of the proposed method.

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Yonggang Jin, Farzin Mokhtarian, Miroslaw Bober, John Illingworth
• Keywords: Computer Vision, CVPR 2008, Fuzzy Chamfer Distance, Fuzzy Objective Functions, Probabilistic Formulation