Real-Time Stereo Vision Applications

Abstract

The stereo correspondence problem comprises an active wide range of research. Many efforts have been made towards efficient solutions to address the various issues of stereo matching. As the improvements in computational resources steadily increase, the demand for real-time applications is getting compulsory. This chapter focuses on the latest improvements in the area of real-time stereo vision. Area-based techniques prove to be more appropriate, handling the stereo correspondence problem aiming at real-time speeds. Their straightforward implementation in hardware enables them suitable in numerous applications such as high-speed tracking and mobile robots, object recognition and navigation, biometrics, vision-guided robotics, threedimensional modelling and many more. Phase-based techniques also allow for efficient realization of such systems, requiring though slightly more complex design methodologies. Additionally, it must be noted that there are many other stereo vision techniques that were not covered by this work, due to the fact that they are mainly targeted in software-based platforms presenting higher processing times, not suitable for real-time operations. FPGA implementations handling the stereo matching problem can be a promising alternative towards real-time speeds. Their uniqueness relies on their architecture and the design methodologies available. Parallel-pipelined processing is able to present great computational capabilities, providing with proper scalability opposed to the serial behaviour of most software-based techniques. On the other hand considering their significantly small volume, low cost, and extensive reconfigurability, they can be oriented towards embedded applications where space and power are significant concerns.