Abstract
We propose a new algorithm for object tracking in crowded video scenes by exploiting the properties of undecimated wavelet packet transform (UWPT) and interframe texture analysis. The algorithm is initialized by the user through specifying a region around the object of interest at the reference frame. Then, coefficients of the UWPT of the region are used to construct a feature vector (FV) for every pixel in that region. Optimal search for the best match is then performed by using the generated FVs inside an adaptive search window. Adaptation of the search window is achieved by interframe texture analysis to find the direction and speed of the object motion. This temporal texture analysis also assists in tracking of the object under partial or short-term full occlusion. Moreover, the tracking algorithm is robust to Gaussian and quantization noise processes. Experimental results show that the proposed algorithm has good performance for object tracking in crowded scenes on stairs, in airports, or at train stations in the presence of object translation, rotation, small scaling, and occlusion.
Highlights
Object tracking is one of the challenging problems in image and video processing applications
It is based on feature vectors generated via the coefficients of the undecimated wavelet packet transform (UWPT) for target representation/localization and filtering/data association are achieved through an adaptive search window by using an interframe texture analysis scheme
The experimental results of the proposed tracking algorithm have been compared with the conventional wavelet transform (WT) as well as the well-known color histogrambased tracking algorithms with two different matching distance measures, that is, chi-squared and Bhattacharyya
Summary
Object tracking is one of the challenging problems in image and video processing applications. We present a new algorithm for tracking arbitrary user-defined regions that encompass the object of interest in the crowded video scenes It is based on feature vectors generated via the coefficients of the undecimated wavelet packet transform (UWPT) for target representation/localization and filtering/data association are achieved through an adaptive search window by using an interframe texture analysis scheme. The main contribution of this paper is the adaptation of a feature vector generation and block matching algorithm in the UWPT domain [26] for tracking objects [27, 28] in crowded scenes in presence of occlusion [29] and noise [30, 31] It uses an interframe texture analysis scheme [32] to update the search window location for the successive frames.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
