Heterogeneous Computing for Real-Time Stereo Matching

Stereo matching is used in many computer vision applications such as 3D reconstruction, robot navigation, robotic surgery, 3-D video surveillance, and tracking object in 3D space. Real time stereo matching is difficult due to the heavy computation required for matching algorithms. In this paper a CPU/GPU heterogeneous computing platform is used to accelerate the processing and run the system in real time. The availability of GPUs (Graphics Processing Units) with hundreds of parallel processing cores, increases the speed of matching algorithms. In this work a combination between feature based and area based matching techniques is used. Feature based matching is fast while area based is robust and the used technique takes the advantages of the both. The stereo matching algorithms run over GeForce GPU and a real time processing is achieved with speed up to 15 frames/sec.