title: Multicue HMM-UKF for real-time contour tracking.
abstract: We propose an HMM model for contour detection based on multiple visual cues in spatial domain and improve it by joint probabilistic matching to reduce background clutter. It is further integrated with unscented Kalman filter to exploit object dynamics in nonlinear systems for robust contour tracking.
authors.affiliation: Siemens Corporate Research, 755 College Road, East, Princeton, NJ 08540, USA. yunqiang.chen@siemens.com
authors.forename: Yunqiang
authors.initials: Y
authors.lastname: Chen
authors.forename: Yong
authors.initials: Y
authors.lastname: Rui
authors.forename: Thomas S
authors.initials: TS
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003199:Computer Systems; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008390:Markov Chains; D015233:Models, Statistical; D009038:Motion; D010363:Pattern Recognition, Automated / Q000379:methods*