Gain Adaptive Real-Time Stereo Streaming

Abstract

This paper introduces a multi-view stereo matcher that generates depth in real-time from a monocular video stream of a static scene. A key feature of our processing pipeline is that it estimates global camera gain changes in the feature tracking stage and efficiently compensates for these in the stereo stage without impacting the real-time performance. This is very important for outdoor applications where the brightness range often far exceeds the dynamic range of the camera. Real-time performance is achieved by leveraging the processing power of the graphics processing unit (GPU) in addition to the CPU. We demonstrate the effectiveness of our approach on videos of urban scenes recorded by a vehicle-mounted camera with auto-gain enabled.