Real-time mobile object detection using stereo

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...

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Bibliographic Details
Published in2014 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
LanguageEnglish
Published IEEE 01.12.2014
Subjects
Adaptive optics
Estimation
Optical imaging
Prediction methods
Real-time systems
Three-dimensional displays
Uncertainty
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DOI10.1109/ICARCV.2014.7064446

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Summary: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.
DOI:10.1109/ICARCV.2014.7064446