Real-time RGB-D Tracking with Depth Scaling Kernelised Correlation Filters and Occlusion Handling

We present a real-time RGB-D object tracker which manages occlusions and scale changes in a wide variety of scenarios. Its accuracy matches, and in many cases outper-forms, state-of-the-art algorithms for precision and it far exceeds most in speed. We build our algorithm on the existing colour-only KCF tracker which uses the ‘kernel trick ’ to extend correlation filters for fast tracking. We fuse colour and depth cues as the tracker’s features and exploit the depth data to both adjust a given target’s scale and to detect and manage occlusions in such a way as to maintain real-time performance, exceeding on average 35fps when benchmarked on two publicly available datasets. We make our easy-to-extend modularised code available to other researchers.