SORT-SGM: Subpixel optimized real-time semiglobal matching for intelligent vehicles

IEEE Transactions on Vehicular Technology

Volumn 61, Issue 3, 2012, Pages 1032-1042

  Pantilie, Cosmin D ^a   Nedevschi, Sergiu ^a  

^a TECHNICAL UNIVERSITY OF CLUJ NAPOCA   (Romania)

Author keywords

Function approximation; intelligent vehicles; parallel processing; real time; stereo vision

Indexed keywords

ACCURACY ALGORITHMS; AUTOMOTIVE APPLICATIONS; COMPUTE UNIFIED DEVICE ARCHITECTURES; DISPARITY MAP; DISPARITY REFINEMENT; FUNCTION APPROXIMATION; GRAPHICS PROCESSING UNIT; HIGH QUALITY; INTEGRATION STRATEGY; INTENSITY DIFFERENCE; MEMORY BANDWIDTHS; PARALLEL PROCESSING; REAL TIME; REAL-TIME IMPLEMENTATIONS; REAL-WORLD IMAGE; SEMI-GLOBAL MATCHING; STEREO ALGORITHMS; STEREO RECONSTRUCTION; SUB PIXELS; SUBPIXEL INTERPOLATION;

APPROXIMATION ALGORITHMS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; OPTIMIZATION; PROGRAM PROCESSORS; REAL TIME CONTROL; STEREO VISION;

IMAGE MATCHING;

EID: 84858976264     PISSN: 00189545     EISSN: None     Source Type: Journal    
DOI: 10.1109/TVT.2012.2186836     Document Type: Article

References (35)

1. INTERSAFE-2 (Dec. 10, 2010), INTERSAFE-2: Cooperative Intersection Safety. [Online]. Available: Http://www.intersafe-2.eu/public/
2. I. Haller, C. Pantilie, F. Oniga, and S. Nedevschi, "Real-time semiglobal dense stereo solution with improved subpixel accuracy," in Proc. IEEE IV Symp., San Diego, CA, 2010, pp. 369-376.
3. S. K. Gehrig, F. Eberli, and T. Meyer, "A real-time low-power stereo vision engine using semiglobal matching," in Proc. 7th ICVS, Liege, Belgium, 2009, pp. 134-143.
4. I. J. Woodfill, G. Gordon, and R. Buck, "Tyzx DeepSea high-speed stereo vision system," in Proc. Comput. Vis. Pattern Recogn. Conf.,Washington, DC, 2004.
5. F. Oniga and S. Nedevschi, "Processing dense stereo data using elevation maps: Road surface, traffic isle, and obstacle detection," IEEE Trans. Veh. Technol., vol. 59, no. 3, pp. 1172-1182, Mar. 2010.
6. R. Danescu and S. Nedevschi, "Probabilistic lane tracking in difficult road scenarios using stereovision," IEEE Trans. Intell. Transp. Syst., vol. 10, no. 2, pp. 272-282, Jun. 2009.
7. H. Hirschmuller, "Accurate and efficient stereo processing by semiglobal matching and mutual information," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recog., 2005, vol. 2, pp. 807-814.
8. R. Zabih and J. Woodfill, "Nonparametric local transforms for computing visual correspondence," in Proc. 3rd Eur. Conf. Comput. Vis., Stockholm, Sweden, 1994, vol. II, pp. 151-158.
9. D. Scharstein and R. Szeliski, "A taxonomy and evaluation of dense twoframe stereo correspondence algorithms," Int. J. Comput. Vis., vol. 47, no. 1-3, pp. 7-42, Apr.-Jun. 2002.
10. M. Z. Brown, D. Burschka, and G. D. Hager, "Advances in computational stereo," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 8, pp. 993-1008, Aug. 2003.
11. S. K. Gehrig and C. Rabe, "Real-time semiglobal matching on the CPU," in Proc. IEEE Comput. Soc. Conf. CVPRW, San Francisco, CA, 2010, pp. 85-92.
12. I. Ernst and H. Hirschmuller, "Mutual information based semiglobal stereo matching on the GPU," in Proc. Adv. Vis. Comput. Pt. I, 2008, vol. 5358, pp. 228-239.
13. Q. Tian andM. N. Huhns, "Algorithms for subpixel registration," Comput. Vis. Graph. Image Process., vol. 35, pp. 220-233, Aug. 1986.
14. R. B. Fisher and D. K. Naidu, "A comparison of algorithms for subpixel peak detection," in Image Technology, Advances in Image Processing, Multimedia and Machine Vision. New York: Springer-Verlag, 1996, pp. 385-404.
15. M. Shimizu and M. Okutomi, "Precise subpixel estimation on areabased matching," in Proc. 8th IEEE Int. Conf. Comput. Vis., 2001, vol. 1, pp. 90-97.
16. S. K. Gehrig and U. Franke, "Improving stereo subpixel accuracy for long range stereo," in Proc. IEEE 11th ICCV, Rio de Janeiro, Brazil, 2007, pp. 1-7.
17. R. Szeliski and D. Scharstein, "Sampling the disparity space image," IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 3, pp. 419-425, Mar. 2004.
18. D. Nehab, S. Rusinkiewiez, and J. Davis, "Improved subpixel stereo correspondences through symmetric refinement," in Proc. 10th IEEE Int. Conf. Comput. Vis., 2005, vol. 1, pp. 557-563.
19. A. N. Stein, A. Huertas, and L. Matthies, "Attenuating stereo pixel-locking via affine window adaption," in Proc. Int. Conf. Robot. Autom., 2006, pp. 914-921.
20. H. Hirschmüller and D. Scharstein, "Evaluation of stereo matching costs on images with radiometric differences," IEEE Trans. Pattern Anal.Mach. Intell., vol. 31, no. 9, pp. 1582-1599, Sep. 2009.
21. H. Hirschmuller and S. Gehrig, "Stereo matching in the presence of subpixel calibration errors," in Proc. IEEE Conf. CVPR, 2009, vol. 1-4, pp. 437-444.
22. I. Haller and S. Nedevschi, "GPU optimization of the SGM stereo algorithm," in Proc. IEEE Int. Conf. ICCP, Cluj-Napoca, Romania, 2010, pp. 197-202.
23. S. Hermann, S. Morales, and R. Klette, "Half-resolution semiglobal stereo matching," in Proc. IEEE IV Symp., Baden-Baden, Germany, 2011.
24. H. Hirschmuller, P. R. Innocent, and J. Garibaldi, "Real-time correlationbased stereo vision with reduced border errors," Int. J. Comput. Vis., vol. 47, no. 1-3, pp. 229-246, Apr.-Jun. 2002.
25. K. Mühlmann, D. Maier, J. Hesser, and R. Männer, "Calculating dense disparity maps from color stereo images: An efficient implementation," Int. J. Comput. Vis., vol. 47, no. 1-3, pp. 79-88, Apr./Jun. 2002.
26. W. Van der Mark and D. M. Gavrila, "Real-time dense stereo for intelligent vehicles," IEEE Trans. Intell. Transp. Syst., vol. 7, no. 1, pp. 38-50, Mar. 2006.
27. R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed. Boston, MA: Addison-Wesley Longman, 2001.
28. I. Haller, C. Pantilie, T. Marita, and S. Nedevschi, "Statistical method for subpixel interpolation function estimation," in Proc. 13th Int. IEEE ITSC, Funchal, Portugal, 2010, pp. 1098-1103.
29. S. Bota and S. Nedevschi, "GLSCENEINT: A synthetic image generation tool for testing computer vision systems," in Proc. IEEE 2nd Int. Conf. Intell. Comput. Commun. Process., Cluj-Napoca, Romania, 2006, pp. 39-44.
30. S. Morales, T. Vaudrey, and R. Klette, "Robustness evaluation of stereo algorithms on long stereo sequences," in Proc. IEEE Intell. Veh. Symp., 2009, vol. 1/2, pp. 347-352.
31. D. Pfeiffer, S. Morales, A. Barth, and U. Franke, "Ground truth evaluation of the Stixel representation using laser scanners," in Proc. 13th Int. IEEE ITSC, Funchal, Portugal, 2010, pp. 1091-1097.
32. H. Hirschmuller, "Stereo vision in structured environments by consistent semiglobal matching," in Proc. IEEE Conf. CVPR, 2006, pp. 2386-2393.
33. NVIDIA, NVIDIA's Next-Generation CUDA Compute Architecture: Fermi, 2009.
34. C. G. Keller, M. Enzweiler, M. Rohrbach, D. F. Llorca, C. Schnörr, and D. M. Gavrila, "The benefits of dense stereo for pedestrian detection," IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, pp. 1096-1106, Dec. 2011.
35. S. Nedevschi, R. Danescu, T. Marita, F. Oniga, C. Pocol, S. Bota, M. M. Meinecke, and M. A. Obojski, "Stereovision-based sensor for intersection assistance," in Advanced Microsystems for Automotive Applications. Berlin, Germany: Springer-Verlag, 2009, pp. 129-163.