A Calibration Method for Binocular Vision System Based on CPSO-BP Netural Network

Abstract:

This paper presents a new calibration method for binocular vision system, based on CPSO-BP neural network. Firstly, the training set of the back propagation (BP) neural network is formed by the image feature point extracted from the binocular vision system. Then the cooperate particle swarm optimization (CPSO) algorithm is introduced to optimize the weights of the BP neural network, making the network with a stronger ability of the global optimization. Experimental results demonstrate that the proposed CPSO-BP-based algorithm has a higher calibration precision than the traditional BP-based calibration method.

• Periodical: Applied Mechanics and Materials (Volumes 490-491)
• Pages: 1686-1691
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.490-491.1686
• Online since: January 2014
• Authors: Jun Zhou*, Tao Xia, Ting Ting Wang, Hua Li Li, Yu Ping Fu
• Keywords: Binocular Vision, Camera Calibration, CPSO, Neural Network (NN)

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