Real-time accurate stereo with bitwise fast voting on CUDA

2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

Volumn , Issue , 2009, Pages 794-800

  Zhang, Ke ^a,b   Lu, Jiangbo ^a,b   Lafruit, Gauthier ^a   Lauwereins, Rudy ^a,b   Van Gool, Luc ^b  

^a IMEC   (Belgium)

^b UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTE UNIFIED DEVICE ARCHITECTURES; COMPUTING RESOURCE; DATA PARALLELISM; FINE GRANULARITY; LOCAL ALGORITHM; MEMORY ACCESS; MULTI-VIEWS; ON CHIPS; REAL-TIME DESIGN; ROBOTICS SYSTEMS; SHARED MEMORIES; SPEED-UP FACTORS; STEREO MATCHING; STEREO METHOD; TIME-ACCURATE; VOTING METHOD;

COMPUTER VISION; PROGRAM PROCESSORS;

DESIGN;

EID: 77953224019     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCVW.2009.5457623     Document Type: Conference Paper

References (15)

1. Middlebury stereo vision page. http://vision.middlebury.edu/stereo/.
2. Nvidia CUDA. http://developer.nvidia.com/object/cuda.html.
3. Open computing language. http://www.khronos.org/opencl.
4. OpenVIDIA. http://openvidia.sourceforge.net/index.php.
5. J. Gibson and O. Marques. Stereo depth with a unified architecture GPU. In Proc. CVPRW, 2008.
6. J. Lu, K.Zhang, G. Lafruit, and F. Catthoor. Real-time stereo matching: a cross-based local approach. In Proc. ICASSP, 2009.
7. J. Owens, M. Houston, D. Luebke, S. Green, J. Stone, and J. Phillips. GPU computing. Proceedings of the IEEE, 96(5):879-899, May 2008.
8. V. Podlozhnyuk. Histogram calculation in CUDA. In NVIDIA Tech. Report, 2007.
9. V. Podlozhnyuk. Image convolution with CUDA. In NVIDIA Tech. Report, 2007.
10. F. Porikli. Integral histogram: a fast way to extract histograms in cartesian spaces. In Proc. IEEE CVPR, 2005.
11. S. Ryoo, C. Rodrigues, S. Baghsorkhi, S. Stone, D. Kirk, and W. Hwu. Optimization principles and application performance evaluation of a multithreaded GPU using CUDA. In Proc. 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming, 2008.
12. D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. IJCV, 47(1):7-42, May 2002.
13. L. Wang, M. Liao, M. Gong, R. Yang, and D. Nister. High quality real-time stereo using adaptive cost aggregation and dynamic programming. In Proc. 3DPVT, 2006.
14. Q. Yang, L. Wang, R. Yang, S. Wang, M. Liao, and D. Nister. Real-time global stereo matching using hierarchical belief propagation. In Proc. BMVC, 2006.
15. K. Zhang, J. Lu, and G. Lafruit. Cross-based local stereo matching using orthogonal integral images. TCSVT, 19(7):1073-1079, July 2009.