Disparity disambiguation by fusion of signal- and symbolic-level information

Machine Vision and Applications

Volumn 23, Issue 1, 2012, Pages 65-77

  Ralli, Jarno ^a   Díaz, Javier ^a   Kalkan, Sinan ^b   Krüger, Norbert ^c   Ros, Eduardo ^a  

^a UNIVERSITY OF GRANADA   (Spain)

^b MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

^c UNIVERSITY OF SOUTHERN DENMARK   (Denmark)

Author keywords

Disparity disambiguation; Disparity fusion; Feed back loop; Low and symbolic level fusion; Signal symbol loop

Indexed keywords

DENSE DISPARITY MAPS; DISPARITY DISAMBIGUATION; FEED-BACK LOOP; FUSION PROCESS; HIGH CONFIDENCE; LOW-LEVEL CUES; MULTI-MODAL IMAGE; RESOLVING AMBIGUITIES; SIGNAL-SYMBOL LOOP;

COMPUTER VISION; HARDWARE; MACHINERY;

STEREO VISION;

EID: 84857049343     PISSN: 09328092     EISSN: 14321769     Source Type: Journal    
DOI: 10.1007/s00138-010-0266-z     Document Type: Article

References (28)

1. A. Darabiha W. MacLean J. Rose 2006 Reconfigurable hardware implementation of a phase-correlation stereoalgorithm Mach. Vis. Appl. 17 2 116 132 10.1007/s00138-006-0018-2
2. Díaz, J.: Multimodal bio-inspired vision system. High performance motion and stereo processing architecture. PhD thesis, University of Granada, Spain (2006)
3. J. Díaz E. Ros R. Carillo A. Prieto 2006 Real-time system for high-image-resolution disparity IEEE Trans. Image Process. 16 280 285 10.1109/TIP.2006.884931
4. M. Felsberg S. Kalkan N. Krüger 2009 Continuous characterization of image structures of different dimensionality Image Vis. Comput. 27 6 628 636 10.1016/j.imavis.2008.06.018
5. Fitzgibbon, A.W.; Zisserman, A.: Multibody Structure and Motion: 3-D Reconstruction of Independently Moving Objects. Lecture Notes in Computer Science, vol. 1842, pp. 891-906 (2000)
6. D. Fleet A. Jepson 1991 Phase-based disparity measurement Comput. Vis. Graph. Image Process. 53 2 198 210 0774.68115
7. D. Fleet A. Jepson 1993 Stability of phase information IEEE Trans. Pattern Anal. Mach. Intell. 15 12 1253 1268 10.1109/34.250844
8. T. Gautama M.V. Hulle 2002 A phase-based approach to the estimation of the optical flow field using spatial filtering IEEE Trans Neural Netw. 13 1127 1136 10.1109/TNN.2002.1031944
9. D. Hubel T. Wiesel 1969 Anatomical demonstration of columns in the monkey striate cortex Nature 221 747 750 10.1038/221747a0
10. Kalkan, S.; Yan, S.; Krüger, V.; Wörgötter, F.; Krüger, N.: A signal-symbol loop mechanism for enhanced edge extraction. In: International Conference on Computer Vision Theory and Applications VISAPP'08, pp. 214-221 (2008)
11. Krüger, N.: Three dilemmas of signal- and symbol-based representations in computer vision. In: Proceedings of the Workshop Brain, Vision and Artificial Intelligence, vol. 3704, pp. 167-176 (2005)
12. N. Krüger M. Lappe F. Wörgötter 2004 Biologically motivated multi-modal processing of visual primitives Interdiscip. J. Artif. Intell. Simul. Behav. 1 5 417 427
13. M. Lee G. Medioni P. Mordohai 2002 Inference of segmented overlapping surfaces from binocular stereo IEEE Trans. Pattern Anal. Mach. Intell. 24 824 837 10.1109/TPAMI.2002.1008388 (Pubitemid 34669594)
14. Medioni G.; Lee M.; Tang C.: A Computational Framework for Segmentation and Grouping. Elsevier, Amsterdam (2000)
15. P. Mordohai G. Medioni 2006 Stereo using monocular cues within the tensor voting framework IEEE Trans. Pattern Anal. Mach. Intell. 28 968 982 10.1109/TPAMI.2006.129
16. Pugeault N.: Early Cognitive Vision: Feedback Mechanisms for the Disambiguation of Early Visual Representation. Vdm Verlag Dr. Müller, Germany (2008)
17. Pugeault, N.; Wörgötter, F.; Krüger, N.: Multi-modal scene reconstruction using perceptual grouping constraints. In: Proceedings of the 5th IEEE Computer Society Workshop on Perceptual Organization in Computer Vision, New York City, 22 June 2006 (in conjunction with IEEE CVPR 2006)
18. Pugeault, N.; Wörgötter, F.; Krüger, N.: Multi-modal scene reconstruction using preceptual grouping constraints. In: Proceedings of the 5th IEEE Computer Society Workshop on Perceptual Organization in Computer Vision, pp. 195-195 (2006)
19. G. Qian R. Chellappa Q. Zheng 2005 Bayesian algorithms for simultaneous structure from motion estimation of multiple independently moving objects IEEE Trans. Image Process. 14 94 109 2118720 10.1109/TIP.2004.837551 (Pubitemid 40085325)
20. J. Ralli J. Díaz E. Ros 2010 A method for sparse disparity densification using voting mask propagation J. Vis. Commun. Image Represent. 21 1 67 74 10.1016/j.jvcir.2009.08.005
21. Ralli, J.; Díaz, J.; Ros, E.: Spatial and temporal constraints in variational correspondence methods. IEEE Trans. Image Process. (2010, submitted)
22. Rares, A.; Reinders, M.; Hendriks, E.: Image interpretation systems. Tech. rep.; mCCWS project Technical Report (MCCWS 2.1.1.3.C) (1999)
23. Sabatini, S.; Gastaldi, G.; Solari, F.; Pauwels, K.; van Hulle, M.; Diaz, J.; Ros, E.; Pugeault, N.; Krüger, N.: Compact (and accurate) early vision processing in the harmonic space. In: VISAPP (1), vol. 1, pp. 213-220 (2007)
24. Sabatini, S.; Gastaldi, G.; Solari, F.; Pauwels, K.; Van Hulle, M.; Diaz, J.; Ros, E.; Pugeault, N.; Krüger, N.: A compact harmonic code for early vision based on anisotropic frequency channels. Comput. Vis. Image Underst. (2010, accepted)
25. D. Scharstein R. Szeliski 2002 A taxonomy and evaluation of dense two-frame stereo correspondence algorithms Int. J. Comput. Vis. 47 1-3 7 42 1012.68731 10.1023/A:1014573219977 (Pubitemid 34428419)
26. F. Solari S. Sabatini G. Bisio 2001 Fast technique for phase-based disparity estimation with no explicit calculation of phase Electron. Lett. 37 23 1382 1383 10.1049/el:20010941 (Pubitemid 33076149)
27. Y.L. Tang R. Kasturi 1996 Tracking moving objects during low altitude flight Mach. Vis. Appl. 9 20 31 10.1007/BF01246636 (Pubitemid 126572340)
28. Weems, C.C.: Architectural requirements of image understanding with respect to parallel processing. In: Proceedings of the IEEE, vol. 79, no. (4), pp. 537-547 (1991)