Print Email Facebook Twitter A comparative study of fast dense stereo vision algorithms Title A comparative study of fast dense stereo vision algorithms Author Sunyoto, H. van der Mark, W. Gavrila, D.M. Publication year 2004 Abstract With recent hardware advances, real-time dense stereo vision becomes increasingly feasible for general-purpose processors. This has important benefits for the intelligent vehicles domain, alleviating object segmentation problems when sensing complex, cluttered traffic scenes. In this paper, we present a framework ofreal-time dense stereo vision algorithms all based on a SIMD architecture. We distinguish different methodical components and examine their performance-speed trade-off. We furthermore compare the resulting algorithmic variations with an existing public source dynamic programming implementation from OpenCV and with the stereo methods discussed in Sharstein and Szeliski's survey. Unlike the previous, we evaluate all stereo vision algorithms using realistically looking simulated data as well as real data, from complex urban traffic scenes. Subject InformaticsAlgorithmsData acquisitionError analysisIntelligent vehicle highway systemsOptimizationProgram processorsSurveyingTraffic controlComputational costsSingle instruction multiple data (SIMD)Stereo algorithmsSynthetic datasStereo vision To reference this document use: http://resolver.tudelft.nl/uuid:560015da-97f2-4f57-b36d-15d73374bba8 TNO identifier 238010 Source 2004 IEEE Intelligent Vehicles Symposium, 14-17 June 2004, Parma, Conference code: 63502, 319-324 Series IEEE Intelligent Vehicles Symposium, Proceedings Document type conference paper Files To receive the publication files, please send an e-mail request to TNO Library.