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Part-based on-road vehicle detection using hidden random field

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Abstract

This paper addresses the problem of detecting on-road vehicles in still images captured by the on-board cameras. We model this as a labelling inference procedure and incorporate the part-based representation of the rear-ends of vehicle within a hidden random field based probabilistic model. Representing objects with parts inherently good for dealing with occlusions. In the proposed model, the part labels form a hidden layer in the graphical model. Our approaches can automatically find the latent parts without explicit indication during training. The experiment is performed on the database with real images with a promising result.

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Authors and Affiliations

  1. Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, 710049, China

    XueTao Zhang, YongJian He & Fei Wang

  2. Xi’an Communication Institute, Xi’an, 710049, China

    YongJian He

Authors
  1. XueTao Zhang
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  2. YongJian He
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  3. Fei Wang
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Corresponding author

Correspondence to Fei Wang.

Additional information

ZHANG XueTao was born in 1981. He received the bachelor’s degree in information engineering and master’s degree in automation science and technology from Xi’an Jiaotong Unversity, Xi’an, China in 2003 and 2006 respectively. He is now a Ph.D. candidate at Institute of Artificial Intelligence and Robotics in Xi’an Jiaotong University. His research interests include computer vision, pattern recognition, especially the object detection and recognition, probabilistic graphical models.

HE YongJian was born in 1975. He is a Ph.D. candidate at the Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China. Currently, he is a teacher of Xi’an Communication Institute, Xi’an, China. He is an expert of General Staff Innovation Workstation. His research interests include pattern recognition, artificial intelligence, computer vision and image processing.

WANG Fei was born in 1975. He received the master’s degree in communication and information system from Xi’an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi’an, China in 2002 and the Ph.D. degree in pattern recognition and intelligent system from Xi’an Jiaotong University, Xi’an, China in 2009. Currently, he is an associate professor at Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University. His research interests include machine vision, shape matching and retrieval, and computer graphics. Dr. Wang Fei is a member of IEEE Computer Society and a member of CCF YOCSEF.

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Zhang, X., He, Y. & Wang, F. Part-based on-road vehicle detection using hidden random field. Sci. China Inf. Sci. 54, 2522–2529 (2011). https://doi.org/10.1007/s11432-011-4493-3

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  • DOI: https://doi.org/10.1007/s11432-011-4493-3

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