Title :
Commentary Paper 2 on "A Probabilistic Bayesian Framework for Model-Based Object Tracking Using Undecimated Wavelet Packet Descriptors"
Author_Institution :
Electr. & Comput. Eng. Dept., Univ. of Michigan-Dearborn, Dearborn, MI
Abstract :
This uses combination of corner-based model and coefficients of undecimated wavelet packet transform (UWPT) for the proposed probabilistic Bayesian framework for object tracking. The UWPT coefficients are calculated for patch around each corner. The proposed scheme uses local descriptors e.g. UWPT coefficients, to improve global representation of object shape model. The proposed scheme then estimates global position of the object using voting based on coherency among the model corners.
Keywords :
Bayes methods; object detection; wavelet transforms; model-based object tracking; object shape model; probabilistic Bayesian framework; undecimated wavelet packet descriptors; Bayesian methods; Layout; Robotics and automation; Shape; Signal processing algorithms; Surveillance; Videoconference; Voting; Wavelet packets; Wavelet transforms;
Conference_Titel :
Advanced Video and Signal Based Surveillance, 2008. AVSS '08. IEEE Fifth International Conference on
Conference_Location :
Santa Fe, NM
Print_ISBN :
978-0-7695-3341-4
Electronic_ISBN :
978-0-7695-3422-0
DOI :
10.1109/AVSS.2008.43