Title :
Multicue HMM-UKF for real-time contour tracking
Author :
Yunqiang Chen ; Yong Rui ; Huang, T.S.
Author_Institution :
Siemens Corp. Res., Princeton, NJ
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
Keywords :
Kalman filters; clutter; edge detection; hidden Markov models; image matching; nonlinear systems; HMM model; background clutter; contour detection; joint probabilistic matching; multiple visual cues; nonlinear systems; real-time contour tracking; unscented Kalman filter; Application software; Hidden Markov models; Human computer interaction; Nonlinear dynamical systems; Nonlinear systems; Object detection; Particle filters; Robustness; Shape; State-space methods; HMM; Parametric contour; joint probabilistic matching.; unscented Kalman filters; Algorithms; Artificial Intelligence; Computer Simulation; Computer Systems; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Markov Chains; Models, Statistical; Motion; Pattern Recognition, Automated;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2006.190
