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
Informatics
Algorithms
Data acquisition
Error analysis
Intelligent vehicle highway systems
Optimization
Program processors
Surveying
Traffic control
Computational costs
Single instruction multiple data (SIMD)
Stereo algorithms
Synthetic datas
Stereo 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