Weighted semi-global matching and center-symmetric census transform for robust driver assistance

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8048 LNCS, Issue PART 2, 2013, Pages 34-41

  Spangenberg, Robert ^a   Langner, Tobias ^a   Rojas, Raúl ^a  

^a FREIE UNIVERSITÄT BERLIN   (Germany)

Author keywords

census transform; local binary pattern; matching costs; semi global matching; stereo vision

Indexed keywords

AUTOMOTIVE APPLICATIONS; CENSUS TRANSFORMS; CENTER-SYMMETRIC LOCAL BINARY PATTERNS; FAST MATCHING ALGORITHM; LOCAL BINARY PATTERNS; SEMI-GLOBAL MATCHING; SMOOTHNESS CONSTRAINTS; THREE-DIMENSIONAL STRUCTURE;

ALGORITHMS; AUTOMOBILE DRIVERS; CONTENT BASED RETRIEVAL; IMAGE ANALYSIS; STEREO VISION; SURVEYS;

IMAGE MATCHING;

EID: 84884484840     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40246-3_5     Document Type: Conference Paper

References (16)

1. Hirschmuller, H.: Stereo processing by semiglobal matching and mutual information. IEEE Trans. Pattern Anal. Mach. Intell. 30(2), 328-341 (2008)
2. Hermann, S., Klette, R.: Iterative semi-global matching for robust driver assistance systems. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds.) ACCV 2012, Part III. LNCS, vol. 7726, pp. 465-478. Springer, Heidelberg (2013)
3. Gehrig, S.K., Franke, U.: Improving stereo sub-pixel accuracy for long range stereo. In: ICCV, pp. 1-7. IEEE (2007)
4. Gehrig, S.K., Eberli, F., Meyer, T.: A real-time low-power stereo vision engine using semi-globalmatching. In: Fritz,M., Schiele, B., Piater, J.H. (eds.) ICVS 2009. LNCS, vol. 5815, pp. 134-143. Springer, Heidelberg (2009)
5. Ernst, I., Hirschmüller, H.: Mutual information based semi-global stereo matching on the GPU. In: Bebis, G., et al. (eds.) ISVC 2008, Part I. LNCS, vol. 5358, pp. 228-239. Springer, Heidelberg (2008)
6. Gehrig, S.K., Rabe, C.: Real-Time Semi-Global Matching on the CPU. In: CVPR Workshops, San Francisco, CA, USA, pp. 85-92 (June 2010)
7. Geiger, A., Roser, M., Urtasun, R.: Efficient large-scale stereo matching. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part I. LNCS, vol. 6492, pp. 25-38. Springer, Heidelberg (2011)
8. Cremers, D., Kohlberger, T., Schnörr, C.: Nonlinear shape statistics in mumfordshah based segmentation. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part II. LNCS, vol. 2351, pp. 93-108. Springer, Heidelberg (2002)
9. Hirschmüller, H., Scharstein, D.: Evaluation of stereo matching costs on images with radiometric differences. IEEE Trans. Pattern Anal. Mach. Intell. 31(9), 1582-1599 (2009)
10. Hirschmüller, H., Gehrig, S.K.: Stereo matching in the presence of sub-pixel calibration errors. In: CVPR, pp. 437-444. IEEE (2009)
11. Zinner, C., Humenberger,M., Ambrosch, K., Kubinger,W.: An optimized software-based implementation of a census-based stereo matching algorithm. In: Bebis, G., et al. (eds.) ISVC 2008, Part I. LNCS, vol. 5358, pp. 216-227. Springer, Heidelberg (2008)
12. Heikkilä, M., Pietikäinen, M., Schmid, C.: Description of interest regions with local binary patterns. Pattern Recogn. 42(3), 425-436 (2009)
13. Meena, K., Suruliandi, A.: Local binary patterns and its variants for face recognition. In: 2011 International Conference on Recent Trends in Information Technology (ICRTIT), pp. 782-786 (June 2011)
14. Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971-987 (July)
15. Geiger, A., Lenz, P., Urtasun, R.: Are we ready for autonomous driving? the kitti vision benchmark suite. In: CVPR, pp. 3354-3361. IEEE (2012)
16. Banz, C., Pirsch, P., Blume, H.: Evaluation of penalty functions for semi-global matching cost aggregation. ISPRS XXXIX-B3, 1-6 (2012)