Dynamic stereo vision system for real-time tracking

Abstract

Biologically-inspired dynamic vision sensors have been introduced in 2002 which asynchronously detect the significant relative light intensity changes in a scene and output them in a form of Address-Event representation. These vision sensors capture dynamical discontinuities on-chip for a reduced data volume compared to that from intensity images. Therefore, they support detection, segmentation and tracking of moving objects in the Address-Event space by exploiting the generated events, as a reaction to intensity changes, resulting from the scene dynamics. Object tracking has been previously demonstrated and reported in scientific publications using monocular dynamic vision sensors. This paper contributes with presenting and demonstrating a tracking algorithm using the 3D sensing technology based on the stereo dynamic vision sensor. This system is capable of detecting and tracking persons within a 4m range at an effective refresh rate of the depth map of up to 200 per second. The 3D system is evaluated for people tracking and the tests showed that up to 60k Address-Events/s can be processed for real-time tracking.