How Far Can We Go with Local Optimization in Real-Time Stereo Matching

Applications such as robot navigation and augmented reality require high-accuracy dense disparity maps in real-time and online. Due to time constraint, most realtime stereo applications rely on local winner-take-all optimization in the disparity computation process. These local approaches are generally outperformed by offline global optimization based algorithms. However, recent research shows that, through carefully selecting and aggregating the matching costs of neighboring pixels, the disparity maps produced by a local approach can be more accurate than those generated by many global optimization techniques. We are therefore motivated to investigate whether these cost aggregation approaches can be adopted in real-time stereo applications and, if so, how well they perform under the real-time constraint. The evaluation is conducted on a real-time stereo platform, which utilizes the processing power of programmable graphics hardware. Several recent cost aggregation approaches are also...

• Type: Conference
• Year: 2006
• Where: 3DPVT
• Authors: Liang Wang, Mingwei Gong, Minglun Gong, Ruigang Yang
• Keywords: 3DPVT 2006, Aggregation Approaches, Applied Computing, Cost Aggregation Approaches, Disparity Maps