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Mobile robots as well as tomorrows intelligent vehicles acting in complex dynamic environments must be able to detect both static and moving obstacles. In intersections or crowded urban areas this task proves to be highly demanding. Stereo vision has been extensively used for this task, as it provides a large amount of data. Since it does not reveal any motion information, static and dynamic objects...
One of the most important step in precisely optical flow computation is using L1 norm for mathematical modeling. For discrete signals, L1 norm gives better results than L2. Another useful ingredient is using local and global combinations in order to use the advantages of both methods. We will present a combined local-global approach that uses L1 norm for both the data fidelity terms and the regularization...
This paper presents an original method for increasing the accuracy of ego vehicle motion estimation using video data. Our algorithm takes as input a monocular video sequence on which originally combines procedures for feature detection and filtering, optical flow, epipolar geometry and estimation of the rotation from the obtained essential matrix. Imposing a movement constraint on the rotation matrix,...
This paper presents an original and practical method for estimating the rotation and the translation of a vehicle using video data. Imposing a movement constraint on the rotation matrix, we obtain a powerful method for estimating the rotation of the vehicle from frame to frame. Our algorithm takes as input a monocular video sequence on which originally combines procedures for feature detection and...
Pedestrians are the most vulnerable participants in urban traffic. The first step toward protecting pedestrians is to reliably detect them. We present a new approach for standing- and walking-pedestrian detection, in urban traffic conditions, using grayscale stereo cameras mounted on board a vehicle. Our system uses pattern matching and motion for pedestrian detection. Both 2-D image intensity information...
In this paper we present a vehicle tracking particle filter system based on gray histogram and sparse optical flow detection in stereo images. The proposed approach is based on the fact that for 2D tracked features we can compute their 3D correspondences, which are used for particle filter tracking improvement. The goal of this paper is to show how vision based particle filter tracking, optical flow...
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