Paper Title:
Realtime On-Road Vehicle Detection Approach Based on Cascaded Structure
  Abstract

Realtime on-road vehicle detection is a key technology in many transportation applications, such as driver assistance, autonomous driving and active safety. A vehicle detection algorithm based on cascaded structure is introduced. Haar-like features are used to built model in this application, and GAB algorithm is chosen to train the strong classifiers. Then, the real-time on-road vehicle classifier based on cascaded structure is constructed by combining the strong classifiers. Experimental results show that the cascaded classifier is excellent in both detection accuracy and computational efficiency, which ensures its application to collision warning system.

  Info
Periodical
Edited by
Han Zhao
Pages
2429-2432
DOI
10.4028/www.scientific.net/AMM.130-134.2429
Citation
L. X. Zhang, X. Y. Qiu, Z. L. Zhang, Y. L. Wang, "Realtime On-Road Vehicle Detection Approach Based on Cascaded Structure", Applied Mechanics and Materials, Vols. 130-134, pp. 2429-2432, 2012
Online since
October 2011
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