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StereoBox: A Robust and Efficient Solution for Automotive Short-Range Obstacle Detection

Abstract

This paper presents a robust method for close-range obstacle detection with arbitrarily aligned stereo cameras. System calibration is performed by means of a dense grid to remove perspective and lens distortion after a direct mapping between image pixels and world points. Obstacle detection is based on the differences between left and right images after transformation phase and with a polar histogram, it is possible to detect vertical structures and to reject noise and small objects. Found objects' world coordinates are transmitted via CAN bus; the driver can also be warned through an audio interface. The proposed algorithm can be useful in different automotive applications, requiring real-time segmentation without any assumption on background. Experimental results proved the system to be robust in several envitonmental conditions. In particular, the system has been tested to investigate presence of obstacles in blind spot areas around heavy goods vehicles (HGVs) and has been mounted on three different prototypes at different heights.

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Correspondence to Alberto Broggi.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Broggi, A., Medici, P. & Porta, P.P. StereoBox: A Robust and Efficient Solution for Automotive Short-Range Obstacle Detection. J Embedded Systems 2007, 070256 (2007). https://doi.org/10.1155/2007/70256

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Keywords

  • Electronic Circuit
  • Direct Mapping
  • Blind Spot
  • Automotive Application
  • System Calibration