Intelligent learning algorithm for depth detection applied to a humanoid vision system

• Main Authors: Pei-Jung Chang, 張倍榕
• Other Authors: Yon-Ping Chen
• Format: Others
• Language: en_US
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/dz5sy3

碩士 === 國立交通大學 === 電機與控制工程系所 === 96 === Stereo–pair images obtained from two cameras can be utilized to compute world coordinate points by using triangulation. However, there are some restrictions from cameras and parameters need to be experimentally obtained, by applying this method. This thesis proposed that, for stereo vision applications which need to evaluate the actual depth, artificial neural networks be used to train the system such that the need for parameters of cameras are eliminated. The training set for our neural network consists of a variety of points in stereo-pair and their corresponding world coordinates. The percentage error obtained from the proposed architecture set-up is comparable with those obtained through traditional depth detection algorithm and that the system is accurate enough for most stereo vision applications.