Non-local spatial redundancy reduction for bottom-up saliency estimation

Journal of Visual Communication and Image Representation

Volumn 23, Issue 7, 2012, Pages 1158-1166

  Wu, Jinjian ^a   Qi, Fei ^a   Shi, Guangming ^a   Lu, Yongheng ^a  

^a XIDIAN UNIVERSITY   (China)

Author keywords

Bottom up visual saliency; Entropy; Human visual system; Image structure; Non local; Redundancy reduction; Self similarity; Visual attention

Indexed keywords

HUMAN VISUAL SYSTEM; IMAGE STRUCTURES; NONLOCAL; SELF-SIMILARITIES; VISUAL ATTENTION; VISUAL SALIENCY;

ENTROPY; VISUALIZATION;

REDUNDANCY;

EID: 84865322616     PISSN: 10473203     EISSN: 10959076     Source Type: Journal    
DOI: 10.1016/j.jvcir.2012.07.010     Document Type: Article

References (50)

1. O. Le Meur, P. Le Callet, D. Barba, and D. Thoreau A coherent computational approach to model bottom-up visual attention IEEE Trans. Pattern Anal. Mach. Intell. 28 5 2006 802 817
2. J.-S. Lee, F.D. Simone, and T. Ebrahimi Efficient video coding based on audio-visual focus of attention J. Visual Commun. Image Represent. 22 8 2011 704 711
3. U. Rutishauser, D. Walther, C. Koch, and P. Perona Is bottom-up attention useful for object recognition? Proc. IEEE Conf. Comput. Vision Pattern Recognit. 2 2004 37 44
4. L. Shao, and M. Brady Invariant salient regions based image retrieval under viewpoint and illumination variations J. Visual Commun. Image Represent. 17 6 2006 1256 1272 (Pubitemid 44854546)
5. T. Chen, M.-M. Cheng, P. Tan, A. Shamir, and S.-M. Hu Sketch2photo: Internet image montage ACM Trans. Graph. 28 5 2009 124:1 124:10
6. L. Itti, Models of bottom-up and top-down visual attention, Ph.D. dissertation, California Institute of Technology, Pasadena, California, January 2000.
7. G.-X. Zhang, M.-M. Cheng, S.-M. Hu, and R.R. Martin A shape-preserving approach to image resizing Comput. Graph. Forum 28 7 2009 1897 1906
8. J. You, A. Perkis, M.M. Hannuksela, and M. Gabbouj Perceptual quality assessment based on visual attention analysis Proceedings of the 17th ACM International Conference on Multimedia, Ser. MM '09 2009 ACM New York, NY, USA 561 564
9. J. You, J. Korhonen, A. Perkis, and T. Ebrahimi Balancing attended and global stimuli in perceived video quality assessment IEEE Trans. Multimedia 13 6 2011 1269 1285
10. L. Itti, and C. Koch Computational modelling of visual attention Nature Rev. Neurosci. 2 3 2001 194 203 (Pubitemid 33673372)
11. R.J. Peters, A. Iyer, C. Koch, and L. Itti Components of bottom-up gaze allocation in natural scenes J. Vision 5 8 2005 692
12. A. Borji, M.N. Ahmadabadi, B.N. Araabi, and M. Hamidi Online learning of task-driven object-based visual attention control Image Vision Comput. 28 7 2010 1130 1145
13. L. Itti, C. Koch, and E. Niebur A model of saliency-based visual attention for rapid scene analysis IEEE Trans. Pattern Anal. Mach. Intell. 20 11 1998 1254 1259 (Pubitemid 128742001)
14. S. Kastner, and L.G. Ungerleider Mechanisms of visual attention in the human cortex Ann. Rev. Neurosci. 23 2000 315 341 (Pubitemid 30350046)
15. L. Itti Quantifying the contribution of low-level saliency to human eye movements in dynamic scenes Visual Cognit. 12 6 2005 1093 1123 (Pubitemid 41283179)
16. L. Itti, and C. Koch Feature combination strategies for saliency-based visual attention systems J. Electron. Imaging 10 1 2001 161 169 (Pubitemid 32279366)
17. D. Gao, N. Vasconcelos, Discriminant saliency for visual recognition from cluttered scenes, in: Adv. Neural Info. Process. Syst., 2004.
18. T. Judd, K. Ehinger, F. Durand, and A. Torralba Learning to predict where humans look IEEE 12th International Conference on Computer Vision 2009 IEEE 2106 2113
19. S. Lee, K. Kim, J. Kim, M. Kim, and H. Yoo Familiarity based unified visual attention model for fast and robust object recognition Pattern Recognit. 43 3 Mar. 2010 1116 1128
20. C. Koch, and S. Ullman Shifts in selection in visual attention: toward the underlying neural circuitry Human Neurobiol. 4 4 1985 219 227 (Pubitemid 16176695)
21. G. Krieger, I. Rentschler, G. Hauske, K. Schill, and C. Zetzsche Object and scene analysis by saccadic eye-movements: an investigation with higher-order statistics Spatial Vision 13 2-3 2000 201 214 (Pubitemid 32088061)
22. E. Niebur, and C. Koch T.A. Brain, Computational Architectures for Attention 1997 MIT Press
23. A. Yarbus Eye Movements and Vision 1967 Plenum Press
24. P. Reinagel, and A. Zador Natural scene statistics at the centre of gaze Netw. Comput. Neural Syst. 10 4 1999 341 350
25. J.M. Findlay The visual stimulus for saccadic eye movements in human observers Perception 9 1 1980 7 21 (Pubitemid 10095485)
26. T. Kadir, and M. Brady Saliency, scale and image description Int. J. Comput. Vision 45 2 2001 83 105 (Pubitemid 33125858)
27. M. Cheng, G. Zhang, N.J. Mitra, X. Huang, S. Hu, Global contrast based salient region detection, in: Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2011, pp. 409-416.
28. D. Gao, V. Mahadevan, and N. Vasconcelos On the plausibility of the discriminant center-surround hypothesis for visual saliency J. Vision 8 7 2008
29. T. Avraham, and M. Lindenbaum Esaliency (Extended saliency): meaningful attention using stochastic image modeling IEEE Trans. Pattern Anal. Mach. Intell. 32 4 2010 693 708
30. Y. Sun, and R. Fisher Object-based visual attention for computer vision Artif. Intell. 146 1 2003 77 123
31. L. Itti, G. Rees, and J.K. Tsotsos Models of bottom-up attention and saliency Neurobiology of Attention 2005 Elsevier San Diego, CA 576 582
32. J. Harel, C. Koch, and P. Perona Graph-based visual saliency Adv. Neural Info. Process. Syst. 19 2007 545 552
33. T. Liu, J. Sun, N.-N. Zheng, X. Tang, H.-Y. Shum, Learning to detect a salient object, in: Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2007.
34. C.M. Privitera, and L.W. Stark Algorithms for defining visual region-of-interesting: comparison with eye fixations IEEE Trans. Pattern Anal. Mach. Intell. 22 9 2000 970 982
35. D. Gao, S. Han, and N. Vasconcelos Discriminant saliency, the detection of suspicious coincidences, and applications to visual recognition IEEE Trans. Pattern Anal. Mach. Intell. 31 6 2009 989 1005
36. R. Achanta, S. Hemami, F. Estrada, S. Susstrunk, Frequency-tuned salient region detection, in: Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2009, pp. 1597-1604.
37. Z. Li A saliency map in primary visual cortex Trends Cognitive Sci. 6 1 2002 9 16 (Pubitemid 34081841)
38. X. Hou, L. Zhang, Saliency detection: a spectral residual approach, in: Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2007, pp. 1-8.
39. N.D.B. Bruce, and J.K. Tsotsos Saliency, attention, and visual search: an information theoretic approach J. Vision 9 3 2009 1 24
40. C. Liu, P.C. Yuen, and G. Qiu Object motion detection using information theoretic spatio-temporal saliency Pattern Recognit. 42 11 2009 2897 2906
41. S. Guiasu Weighted entropy Rep. Math. Phys. 2 3 1971 165 179
42. A. Buades, B. Coll, J. Morel, A non-local algorithm for image denoising, in: Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2, 2005, pp. 60-65
43. J. Hutchinson Fractals and self-similarity Indiana Univ. Math. J 30 5 1981 713 747
44. S. Alexander, E. Vrscay, S. Tsurumi, A simple, general model for the affine self-similarity of images, in: Image Anal. Recognit., 2008, pp. 192-203.
45. O. Boiman, M. Irani, Detecting irregularities in images and in video, in: 10th IEEE Int. Conf. Computer Vision, 1, 2005, pp. 462-469. (Pubitemid 44054993)
46. J. Maver Self-similarity and points of interest IEEE Trans. Pattern Anal. Mach. Intell. 32 7 2010 1211 1226
47. C. BenAbdelkader, R. Cutler, and L. Davis Gait recognition using image self-similarity EURASIP J. Appl. Signal Process. 2004 572 585
48. J. Van De Weijer, T. Gevers, and A.D. Bagdanov Boosting color saliency in image feature detection IEEE Trans. Pattern Anal. Mach. Intell. 28 1 2006 150 156 (Pubitemid 46395313)
49. J. van de Weijer, T. Gevers, and J. Geusebroek Edge and corner detection by photometric quasi-invariants IEEE Trans. Pattern Anal. Mach. Intell. 27 4 2005 625 630 (Pubitemid 40556116)
50. N.D.B. Bruce. [Online]. Available: .