An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
Stereo Vision-based approaches for Pedestrian Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A featureless and stochastic approach to on-board stereo vision system pose
Image and Vision Computing
A duality based approach for realtime TV-L1 optical flow
Proceedings of the 29th DAGM conference on Pattern recognition
IEEE Transactions on Intelligent Transportation Systems
An Efficient Approach to Onboard Stereo Vision System Pose Estimation
IEEE Transactions on Intelligent Transportation Systems
Space variant representations for mobile platform vision applications
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
A Novel Space Variant Image Representation
Journal of Mathematical Imaging and Vision
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This paper presents a robust technique for estimating on-board monocular vision system pose. The proposed approach is based on a dense optical flow that is robust against shadows, reflections and illumination changes. A RANSAC based scheme is used to cope with the outliers in the optical flow. The proposed technique is intended to be used in driver assistance systems for applications such as obstacle or pedestrian detection. Experimental results on different scenarios, both from synthetic and real sequences, shows usefulness of the proposed approach.