Abstract
Recent local stereo matching methods have achieved comparable performance with global methods. However, the final disparity map still contains significant outliers. In this article, the authors propose a local stereo matching method that employs a new combined cost approach and a secondary disparity refinement mechanism. They formulate combined cost using a modified color census transform and truncated absolute differences of color and gradients. They also use symmetric guided filter for cost aggregation. Unlike in traditional stereo matching, they propose a novel secondary disparity refinement to further remove the remaining outliers. Experimental results on the Middlebury benchmark show that their method ranks fifth out of 153 submitted methods, and it's the best cost-volume filtering-based local method. Experiments on real-world sequences and depth-based applications also validate the proposed method's effectiveness.
Original language | English |
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Pages (from-to) | 16-27 |
Number of pages | 12 |
Journal | IEEE Multimedia |
Volume | 21 |
Issue number | 4 |
Early online date | 9 Sept 2014 |
DOIs | |
Publication status | Published - Oct 2014 |
Bibliographical note
Publisher Copyright:© 2014 IEEE.
Keywords
- Benchmark testing
- Disparity refinement
- Image color analysis
- Image edge detection
- Matching cost
- Multimedia
- Radar
- Research and development
- Stereo matching
- Stereo vision
- Transforms
ASJC Scopus subject areas
- Software
- Signal Processing
- Media Technology
- Hardware and Architecture
- Computer Science Applications