Bus detection and recognition in real transportation scenes is a fundamental task for public security road crossing application. In this paper, a novel system is proposed to overcome the high computation complexity and the hard task of training large set of 3D models of the current algorithms. In the proposed system, the 3D model is built according to the contour information of the vehicle itself so that the system is more robust and practical. Meanwhile, the line features of the vehicle are extracted using the LSD (line segment detector) method. Finally, the line features are matched with the 3D model using a combined matching algorithm which reduces the computational complexity of the matching process. Experiments on real videos show the proposed method has a good performance in terms of the high recall ratio and low fall-out ratio. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Ma, W., Yang, H., & Wang, Y. (2012). A robust bus detection and recognition method based on 3D model and LSD method for public security road crossing application. In Communications in Computer and Information Science (Vol. 331 CCI, pp. 73–81). https://doi.org/10.1007/978-3-642-34595-1_11
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