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Content Provider | IEEE Xplore Digital Library |
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Author | Baker, S. Scharstein, D. Lewis, J.P. Roth, S. Black, M.J. Szeliski, R. |
Copyright Year | 2007 |
Description | Author affiliation: Microsoft Res., Redmond, WA (Baker, S.) |
Abstract | The quantitative evaluation of optical flow algorithms by Barron et al. led to significant advances in the performance of optical flow methods. The challenges for optical flow today go beyond the datasets and evaluation methods proposed in that paper and center on problems associated with nonrigid motion, real sensor noise, complex natural scenes, and motion discontinuities. Our goal is to establish a new set of benchmarks and evaluation methods for the next generation of optical flow algorithms. To that end, we contribute four types of data to test different aspects of optical flow algorithms: sequences with nonrigid motion where the ground-truth flow is determined by tracking hidden fluorescent texture; realistic synthetic sequences; high frame-rate video used to study interpolation error; and modified stereo sequences of static scenes. In addition to the average angular error used in Barron et al., we compute the absolute flow endpoint error, measures for frame interpolation error, improved statistics, and flow accuracy at motion boundaries and in textureless regions. We evaluate the performance of several well-known methods on this data to establish the current state of the art. Our database is freely available on the Web together with scripts for scoring and publication of the results at http://vision.middlebury.edu/flow/. |
Starting Page | 1 |
Ending Page | 8 |
File Size | 1684051 |
Page Count | 8 |
File Format | |
ISBN | 9781424416301 |
ISSN | 15505499 |
DOI | 10.1109/ICCV.2007.4408903 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-10-14 |
Publisher Place | Brazil |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Databases Image motion analysis Optical sensors Optical noise Layout Interpolation Benchmark testing Tracking Fluorescence Fluid flow measurement |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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