Sift features based object tracking with discrete wavelet transform
Yang W.-B.; Fang B.; Tang Y.-Y.; Shang Z.-W.; Li D.-H.
Source Publication2009 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2009
AbstractA novel first-detect-then-identify approach with SIFT features and discrete wavelet transform for tracking object is proposed in real surveillance scenarios. For accurate and fast moving object detection, discrete wavelet transform is adopted to eliminate the noises of the frames which may cause detection errors, and then objects are detected by applying the inter-frame difference method on the low frequency parts of two consecutive frames, and then SIFT feature is used for object representation and identification due to its invariant properties. Experimental results demonstrate that the proposed strategy improves the tracking performance by comparing with the classical mean shift method, and it is also shown that the proposed algorithm can be also applied in multiple objects tracking in real scenarios. © 2009 IEEE.
KeywordDiscrete wavelet transform Moving object detecting Object tracking Scale invariant feature transform
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Cited Times [WOS]:3   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionUniversity of Macau
AffiliationChongqing University
Recommended Citation
GB/T 7714
Yang W.-B.,Fang B.,Tang Y.-Y.,et al. Sift features based object tracking with discrete wavelet transform[C],2009:380-385.
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