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| Content Provider | IET Digital Library |
|---|---|
| Author | Gupta, Raj Kumar Cho, Siu Yeung |
| Abstract | In this study, the authors present a new area-based stereo matching algorithm that computes dense disparity maps for a real-time vision system. Although many stereo matching algorithms have been proposed in recent years, correlation-based algorithms still have an edge because of speed and less memory requirements. The selection of appropriate shape and size of the matching window is a difficult problem for correlation-based algorithms. In the proposed approach, two correlation windows are used to improve the performance of the algorithm while maintaining its real-time suitability. The CPU implementation of the proposed algorithm computes more than 10 frame/s. Unlike other area-based stereo matching algorithms, this method works very well at disparity boundaries as well as in low textured image areas and computes a dense and sharp disparity map. Evaluations on the benchmark Middlebury stereo datasets have been performed to demonstrate the qualitative and quantitative performance of the proposed algorithm. |
| Starting Page | 123 |
| Ending Page | 134 |
| Page Count | 12 |
| ISSN | 17519632 |
| Volume Number | 7 |
| e-ISSN | 17519640 |
| Issue Number | Issue 2, Apr (2013) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-cvi/7/2 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2011.0077 |
| Journal | IET Computer Vision |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Area Based Stereo Matching Computer Vision And Image Processing Technique Correlation Based Algorithm Correlation Method Disparity Boundaries Disparity Maps Fast Stereo Correspondence Image Matching Image Recognition Matching Window Middlebury Stereo Datasets Realtime Vision System Stereo Image Processing Textured Image Areas Window Based Approach |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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