Real-time mobile object detection using stereo

• Published in: 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV) pp. 1021 - 1026
• Main Authors: Derome, Maxime, Plyer, Aurelien, Sanfourche, Martial, Le Besnerais, Guy
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2014
• Subjects: Adaptive optics; Estimation; Optical imaging; Prediction methods; Real-time systems; Three-dimensional displays; Uncertainty
• DOI: 10.1109/ICARCV.2014.7064446

This paper considers passive vision for robotics and focuses on devising a real-time process for moving object detection using a stereo rig. As several previous works, our method relies on the use of dense stereo and of optical flow. Observing that the main computational load of existing methods is related to the estimation of the optical flow, we propose to use a fast algorithm based on Lucas-Kanade's paradigm. We derive a new uncertainty model which explicitly takes into account all errors originating from each estimation step of the process. In contrast with most previous works, we describe a rigorous expansion of the error related to vision based ego-motion estimation. Finally, we present a comparative study of performance on the KITTI dataset, which demonstrates the effectiveness of the proposed approach.