Forward Vehicle Collision Warning Based on Quick Camera Calibration

April 22, 2019 Β· Declared Dead Β· πŸ› IEEE International Conference on Acoustics, Speech, and Signal Processing

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Authors Yuwei Lu, Yuan Yuan, Qi Wang arXiv ID 1904.12642 Category cs.CV: Computer Vision Cross-listed cs.AI Citations 5 Venue IEEE International Conference on Acoustics, Speech, and Signal Processing Last Checked 4 months ago
Abstract
Forward Vehicle Collision Warning (FCW) is one of the most important functions for autonomous vehicles. In this procedure, vehicle detection and distance measurement are core components, requiring accurate localization and estimation. In this paper, we propose a simple but efficient forward vehicle collision warning framework by aggregating monocular distance measurement and precise vehicle detection. In order to obtain forward vehicle distance, a quick camera calibration method which only needs three physical points to calibrate related camera parameters is utilized. As for the forward vehicle detection, a multi-scale detection algorithm that regards the result of calibration as distance priori is proposed to improve the precision. Intensive experiments are conducted in our established real scene dataset and the results have demonstrated the effectiveness of the proposed framework.
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