An optimized Silicon Retina stereo matching algorithm using time-space correlation

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn , Issue , 2011, Pages

  Sulzbachner, Christoph ^a   Zinner, Christian ^a   Kogler, Jurgen ^a  

^a AIT AUSTRIAN INSTITUTE OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

DSP SYSTEM; EVENT-BASED; GRAY-SCALE IMAGES; MATCHING METHODS; MOBILE ARCHITECTURE; MULTI CORE; OPTIMIZED IMPLEMENTATION; PERFORMANCE OPTIMIZATIONS; PRE-PROCESSING; PROCESSOR ARCHITECTURES; RUNTIMES; SENSOR DATA; SENSOR OUTPUT; SILICON RETINA; STEREO MATCHING ALGORITHM; TIME CORRELATIONS; TIME-SPACE;

ALGORITHMS; COMPUTER ARCHITECTURE; COMPUTER VISION; DATA HANDLING; DIGITAL SIGNAL PROCESSORS; MICROPROCESSOR CHIPS; OPTIMIZATION; SENSORS; SIGNAL PROCESSING; STEREO VISION;

IMAGE MATCHING;

EID: 80054916421     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2011.5981722     Document Type: Conference Paper

References (14)

1. C. Posch and D. Matolin and R. Wohlgenannt. A QVGA 143 dB Dynamic Range Frame-Free PWM Image Sensor With Lossless Pixel-Level Video Compression and Time-Domain CDS. IEEE Journal of Solid-State Circuits, 46(1):259-275, 2011.
2. C. Zinner and M. Humenberger and K. Ambrosch and W. Kubinger. An Optimized Software-Based Implementation of a Census-Based Stereo Matching Algorithm. Proceedings of the 4th International Symposium on Visual Computing (ISVC), 2008.
3. M. Humenberger, C. Zinner, M. Weber, W. Kubinger, and M. Vincze. A fast stereo matching algorithm suitable for embedded real-time systems. Computer Vision and Image Understanding Journal (Special Issue on Embedded Vision), 114(11):1080-1202, 2010.
4. Intel Corporation. Intel Integrated Performance Primitives for Intel Architecture. 2007. Document Number: A70805-021US.
5. J. Kramer. An on/off transient imager with event-driven, asynchronous read-out. IEEE International Symposium on Circuits and Systems (ISCAS), 2002.
6. J. Kogler, C. Sulzbachner, and W. Kubinger. Bio-inspired stereo vision system with silicon retina imagers. In Computer Vision Systems, volume 5815 of Lecture Notes in Computer Science, pages 174-183. Springer Berlin / Heidelberg, 2009.
7. C. Mead and M. Mahowald. A silicon model of early visual processing. Neural Networks Journal, 1, 1988.
8. P. Lichtsteiner and C. Posch and T. Delbruck. A 128×128 120dB 30mW asynchronous vision sensor that responds to relative intensity change. Proceedings of the IEEE International Solid-State Circuits Conference, 2006.
9. P. Lichtsteiner and C. Posch and T. Delbruck. A 128×128 120dB 15μ Latency Asynchronous Temporal Contrast Vision Sensor. Proceedings of the IEEE International Solid-State Circuits Conference, 2008.
10. D. Scharstein, R. Szeliski, and R. Zabih. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. Stereo and Multi-Baseline Vision, 2001. (SMBV 2001). Proceedings. IEEE Workshop on, pages 131-140, 2001.
11. S. Schraml, P. Schön, and N. Milosevic. Smartcam for realtime stereo vision - address-event based embedded system. In In: Ranchordas, Alpesh, Arajo, Helder and Vitri, Jordi (eds.) VISAPP 2007 - Proceedings of the Second International Conference on Computer Vision Theory and Applications, volume 2, pages 466-471, Barcelona/Spain, March 2007.
12. O. Schreer. Stereoanalyse und Bildsynthese. Springer Berlin / Heidelberg, 2005.
13. J. Shi and C. Tomasi. Good features to track. IEEE Conference on Computer Vision and Pattern Recognition, pages 593-600, 1994.
14. M. Sivilotti. Wiring consideration in analog VLSI systems with application to field programmable networks. PhD thesis, California Institute of Technology, 1991.