A Lidar and Vision-based Approach for Pedestrian and Vehicle Detection and Tracking
- 1 September 2007
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 21530009,p. 1044-1049
- https://doi.org/10.1109/itsc.2007.4357637
Abstract
This paper presents a sensorial-cooperative architecture to detect, track and classify entities in semi-structured outdoor scenarios for intelligent vehicles. In order to accomplish this task, information provided by in-vehicle Lidar and monocular vision is used. The detection and tracking phases are performed in the laser space, and the object classification methods work both in laser space (using a Gaussian Mixture Model classifier) and in vision spaces (AdaBoost classifier). A Bayesian-sum decision rule is used in order to combine the results of both classification techniques, and hence a more reliable object classification is achieved. Experiments confirm the effectiveness of the proposed architecture.Keywords
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