Publication: Performance measures for video object segmentation and tracking
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KU Authors
Co-Authors
Erdem, Çiğdem Eroğlu
Sankur, Bülent
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Abstract
We propose measures to evaluate quantitatively the performance of video object segmentation and tracking methods without ground-truth (GT) segmentation maps. The proposed measures are based on spatial differences of color and motion along the boundary of the estimated video object plane and temporal differences between the color histogram of the current object plane and its predecessors. They can be used to localize (spatially and/or temporally) regions where segmentation results are good or bad; and/or they can be combined to yield a single numerical measure to indicate the goodness of the boundary segmentation and tracking results over a sequence. The validity of the proposed performance measures without GT have been demonstrated by canonical correlation analysis with another set of measures with GT on a set of sequences (where GT information is available). Experimental results are presented to evaluate the segmentation maps obtained from various sequences using different segmentation approaches.
Source
Publisher
IEEE-Inst Electrical Electronics Engineers Inc
Subject
Computer Science, Artificial intelligence, Electrical electronics engineering
Citation
Has Part
Source
IEEE Transactions on Image Processing
Book Series Title
Edition
DOI
10.1109/TIP.2004.828427