Eighth IEEE International Symposium on Multimedia (ISM'06) Object Detection Based on Weighted Adaptive Prediction in Lifting Scheme Transform San Diego, CA December 11-December 13 ISBN: 0-7695-2746-9
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISM.2006.118
This paper presents a new algorithm for detecting user-selected objects in a sequence of images based on a new weighted adaptive lifting scheme transform. In our algorithm, we first select a set of coefficients as object features in the wavelet transform domain and then build an adaptive transform considering the selected features. The goal of the designed adaptive transform is to "vanish" the selected features as much as possible in the transform domain. After applying both non-adaptive and adaptive transforms to a given test image, the corresponding transform domain coefficients are compared for detecting the object of interest. We have verified our claim with experimental results on 1-D signals and real images.
Citation:
Mahdi Amiri, Hamid R. Rabiee, "Object Detection Based on Weighted Adaptive Prediction in Lifting Scheme Transform," ism, pp.652-656, Eighth IEEE International Symposium on Multimedia (ISM'06), 2006 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||