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Selective-Attention Correlation Measure for Precision Video Tracking Jae-Soo CHO Byoung-Ju YUN Publication IEICE TRANSACTIONS on Information and Systems Vol.E88-D No.5 pp.1041-1049 Publication Date: 2005/05/01 Online ISSN: DOI: 10.1093/ietisy/e88-d.5.1041 Print ISSN: 0916-8532 Type of Manuscript: PAPER Category: Image Recognition, Computer Vision Keyword: correlation-based video tracking, block matching algorithm, selective-attention correlation measure, Full Text: PDF(1.5MB)>>
Summary: In this paper, the false-peaks problem of the conventional correlation-based video tracking is investigated using a simple mathematical analysis. To reduce the false detection problem, a selective-attention correlation measure is proposed. The problem with the conventional correlation measures is that all pixels in the reference block image are equally treated in the computation of the correlation measures irrespective of target or background pixels. Therefore, the more the reference block image includes background pixels, the higher probability of false-peaks is introduced due to the correlation between the background pixels of the reference block and those of the input search image. The proposed selective-attention correlation measure has different consideration according to target and background pixels in the matching process, which conform with the selective-attention property of human visual system. Various computer simulations validated these analyses and confirmed that the proposed selective-attention measure is effective to reduce considerably the probability of the false-peaks. | ||||||||||
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