Journal
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Volume 34, Issue 9, Pages 1744-1757Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TPAMI.2011.236
Keywords
Optical flow; image motion; video motion; variational methods; optimization; features
Funding
- Research Grants Council of the Hong Kong SAR [412911]
- NSF of China [61133009]
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A common problem of optical flow estimation in the multiscale variational framework is that fine motion structures cannot always be correctly estimated, especially for regions with significant and abrupt displacement variation. A novel extended coarse-to-fine (EC2F) refinement framework is introduced in this paper to address this issue, which reduces the reliance of flow estimates on their initial values propagated from the coarse level and enables recovering many motion details in each scale. The contribution of this paper also includes adaptation of the objective function to handle outliers and development of a new optimization procedure. The effectiveness of our algorithm is demonstrated by Middlebury optical flow benchmarkmarking and by experiments on challenging examples that involve large-displacement motion.
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