Title :
Robust Control-Based Object Tracking
Author :
Qu, Wei ; Schonfeld, Dan
Author_Institution :
Siemens Med. Solutions USA, Inc., IL
Abstract :
This correspondence presents a video tracking framework using control-based observer design. It unifies several kernel-based approaches into a consistent theoretical framework by modeling tracking as a recursive inverse problem. The framework relies on observability theory to handle the ldquosingularityrdquo problem and provides explicit criteria for kernel design and dynamics evaluation.
Keywords :
inverse problems; robust control; target tracking; video signal processing; kernel design; object tracking; recursive inverse problem; robust control; video tracking; Application software; Computational complexity; Equations; Filtering; Inverse problems; Kernel; Observability; Optical filters; Particle tracking; Robust control; Object tracking; video analysis; video tracking; Algorithms; Artificial Intelligence; Feedback; Image Enhancement; Image Interpretation, Computer-Assisted; Motion; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Video Recording;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2008.2001391