Stereo vision motion detection from a moving platform

In order for robots to coexist with humans it is important that they are able to see and track them. Simple tasks like moving to avoid a passing human in the corridor require that the robot is able to estimate the position and velocity of the passer. Several systems for tracking people have been presented in the past, however few attempt tracking using vision on a moving platform. In the field of mobile robotics it is important that the methods used in tracking are robust to egomotion. In this paper we present preliminary results of a system which uses basic stereo vision to segment and track moving objects. The system requires the use of both the three dimensional stereo disparity information as well as optical flow to segment and track people. Experimental results showing the removal of optical flow due to egomotion are presented as well as a method for measuring the change in depth over time after compensating for the robots motion. We also present a useful method for judging the quality of the gathered visual data. Finally the capability to track moving people using a Kalman filter is demonstrated.