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A wavelet-based approach to image feature stability assessment
conference contribution
posted on 2006-12-21, 00:00 authored by Antonio Robles-KellyAntonio Robles-Kelly, R GoeckeIn this paper, we present a novel method for assessing image-feature stability. The method hinges on applying the discrete wavelet transform to the image features under study throughout a number of video frames in an image sequence. For purposes of stability assessment, we recover the image-feature vectors for each video frame and then track them trough a series of consecutive frames in the image sequence. We apply the discrete wavelet transform to the time series constructed from the pairwise Euclidean distances for each of the image features under study and use the wavelet transform coefficients to assess their stability. We then recover the stable features by clustering together those time series which exhibit largely constant low-pass wavelet coefficients. We present results of the stability analysis for Harris corners, Maximally Stable Extremal Regions, and Scale Invariant Feature Transform regions extracted from two real-world video sequences. We also elaborate on the applications of our method to indexing, retrieval, and compression of stable image feature vectors. © 2006 IEEE.
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2006Publisher DOI
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1063-6919ISBN-13
9780769526461ISBN-10
0769526462Publication classification
E1.1 Full written paper - refereedTitle of proceedings
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern RecognitionUsage metrics
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