Real-Time Stereo Vision Implementation on Nvidia Jetson TX2

We present a real-time stereo vision system implemented on a low power-consumption Nvidia Jetson TX2 embedded platform with a GPU accelerator. We use a local matching method with Normalized Cross Correlation as the cost function, perform a set of optimisations to reduce computational cost and improve output quality. We use the KITTI dataset to evaluate our system. With image resolution of 1242x375, our system achieves an average of 155 FPS with 90 disparity levels on the TX2 platform.