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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kang Zhang Jiyang Li Yijing Li Weidong Hu Lifeng Sun Shiqiang Yang |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Computer Science, Tsinghua University, Beijing, China (Kang Zhang; Jiyang Li; Yijing Li; Weidong Hu; Lifeng Sun; Shiqiang Yang) |
| Abstract | In this paper, we propose a novel binary-based cost computation and aggregation approach for stereo matching problem. The cost volume is constructed through bitwise operations on a series of binary strings. Then this approach is combined with traditional winner-take-all strategy, resulting in a new local stereo matching algorithm called binary stereo matching (BSM). Since core algorithm of BSM is based on binary and integer computations, it has a higher computational efficiency than previous methods. Experimental results on Middlebury benchmark show that BSM has comparable performance with state-of-the-art local stereo methods in terms of both quality and speed. Furthermore, experiments on images with radiometric differences demonstrate that BSM is more robust than previous methods under these changes, which is common under real illumination. |
| Starting Page | 356 |
| Ending Page | 359 |
| File Size | 933274 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467322164 |
| ISSN | 10514651 |
| e-ISBN | 9784990644109 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-11-11 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | ICPR Org Committee |
| Subject Keyword | Stereo vision Radiometry Computer vision Lighting Pattern recognition Robustness Optimization |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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