Model-Based Hand Tracking by Chamfer Distance and Adaptive Color Learning Using Particle Filter. (29th December 2009)

• Record Type: Journal Article
• Authors: Kerdvibulvech, Chutisant; Saito, Hideo
• Other Names: Roy-Chowdhury Amit Academic Editor.
• Is Part Of: EURASIP journal on image and video processing. Volume 2009(2009)
• Publication Date: 2009-12-29
• Subjects: Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; Traitement d'images; Vidéo numérique; Digital video; Image processing -- Digital techniques; Periodicals; Electronic journal; Electronic journals; 621.367
• DOI: 10.1155/2009/724947
• Languages: English
• ISSNs: 1687-5176

Abstract

Abstract : We propose a new model-based hand tracking method for recovering of three-dimensional hand motion from an image sequence. We first build a three-dimensional hand model using truncated quadrics. The degrees of freedom (DOF) for each joint correspond to the DOF of a real hand. This feature extraction is performed by using the Chamfer Distance function for the edge likelihood. The silhouette likelihood is performed by using a Bayesian classifier and the online adaptation of skin color probabilities. Therefore, it is to effectively deal with any illumination changes. Particle filtering is used to track the hand by predicting the next state of three-dimensional hand model. By using these techniques, this method adds the useful ability of automatic recovery from tracking failures. This method can also be used to track the guitarist's hand.