Cross-comparison census for colour stereo matching applied to intelligent vehicle

作     者：Miron, A. Ainouz, S. Rogozan, A. Bensrhair, A. 

作者机构：INSA Rouen LITIS Lab EA4108 F-76801 Rouen France 

出 版 物：《ELECTRONICS LETTERS》 (电子学快报)

年 卷 期：2012年第48卷第24期

页      面：1530-1531页

核心收录：

学科分类：0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：project Co-Drive FUI 

主　　题：AUTOMOBILES COMPUTER algorithms REAL-time computing AUTOMATIC systems GRAPHICS processing units (Computers) BIG data PIXELS 

摘      要：A fast and efficient colour stereo matching algorithm is presented with intended application to intelligent vehicles. The algorithm is initialised by selecting an appropriate colour space giving the smallest disparity error on a training set. A dynamic cross-based aggregation region is then applied. To be fast and robust to noise and illumination variations, a new technique is proposed for census transform in combination with a sparse mask. The algorithm is accelerated with GPU implementation. The performance of the proposed algorithm has been tested on the reference Middlebury dataset, as well as on simulated road traffic scenes of the TNO MARS/Prescan database.