RARE2012: A multi-scale rarity-based saliency detection with its comparative statistical analysis

Signal Processing: Image Communication

Volumn 28, Issue 6, 2013, Pages 642-658

  Riche, Nicolas ^a   Mancas, Matei ^a   Duvinage, Matthieu ^a   Mibulumukini, Makiese ^a   Gosselin, Bernard ^a   Dutoit, Thierry ^a  

^a UNIVERSITY OF MONS   (Belgium)

Author keywords

Bottom up saliency; Comparative statistical analysis; Multi scale rarity mechanism; Regions of interest; Saliency models evaluation; Visual attention

Indexed keywords

BOTTOM-UP SALIENCIES; MULTISCALES; REGIONS OF INTEREST; SALIENCY MODELS EVALUATION; VISUAL ATTENTION;

ELECTRICAL ENGINEERING; SIGNAL PROCESSING;

STATISTICAL METHODS;

EID: 84878015694     PISSN: 09235965     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.image.2013.03.009     Document Type: Article

References (46)

1. L. Itti, C. Koch, and E. Niebur A model of saliency-based visual attention for rapid scene analysis IEEE Transactions on Pattern Analysis and Machine Intelligence 20 11 1998 1254 1259
2. M. Mancas, F. Pirri, and M. Pizzoli From saliency to eye gaze: embodied visual selection for a pan-tilt-based robotic head Advances in Visual Computing 2011 135 146
3. Ali Borji, Laurent Itti, State-of-the-art in visual attention modeling, IEEE Transactions on Pattern Analysis and Machine Intelligence in press, http://ilab.usc.edu/publications/doc/Borji-Itti12pami.pdf.
4. T. Judd, F. Durand, and A. Torralba A benchmark of computational models of saliency to predict human fixations IEEE Transactions on Pattern Analysis and Machine Intelligence 2012
5. Matei Mancas, Nicolas Riche, Computational attention website, 2012.
6. Y.F. Ma, H.J. Zhang, Contrast-based image attention analysis by using fuzzy growing, in; International Multimedia Conference: Proceedings of the Eleventh ACM International Conference on Multimedia, vol. 2, 2003, pp. 374-381.
7. N. Bruce, J. Tsotsos, Saliency based on information maximization, in: Advances in Neural Information Processing Systems, vol. 18, 2006, pp. 155-162.
8. D. Walther, Interactions of Visual Attention and Object Recognition: Computational Modeling, Algorithms, and Psychophysics, PhD Thesis, California Institute of Technology, 2006.
9. D. Walther, and C. Koch Modeling attention to salient proto-objects Neural Networks 19 9 2006 1395 1407
10. C. Koch J. Harel, P. Perona, Graph-based visual saliency, in: Proceedings of Neural Information Processing Systems (NIPS), 2006.
11. Lei Xu Yin Li, Yue Zhou, Xiaochao Yang, Incremental sparse saliency detection, in: IEEE International Conference on Image Processing (ICIP), 2009.
12. Junchi Yan Yin Li, Yue Zhou, Visual saliency based on conditional entropy, in: The Asian Conference on Computer Vision (ACCV), 2009.
13. Hae Jong Seo, Peyman Milanfar, Nonparametric bottom-up saliency detection by self-resemblance, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1st International Workshop on Visual Scene Understanding (ViSU), June 2009.
14. Hae Jong Seo, and Peyman Milanfar Static and space-time visual saliency detection by self-resemblance Jounal of Vision 9 12-15 2009 1 27
15. M. Cheng, et al., Global contrast based salient region detection, in: IEEE Conference on Computer Vision and Pattern Recognition, June 2011, pp. 409-416.
16. Z. Liu Unsupervised salient object segmentation based on kernel density estimation and two-phase graph cut IEEE Transactions on Multimedia 14 August (4) 2012 1275 1289
17. F. Perazzil et al., Saliency filters: contrast based filtering for salient region detection, in: IEEE Conference on Computer Vision and Pattern Recognition, June 2012, pp. 1-8.
18. Antonio Torralba, Aude Oliva, Monica Castelhano, and John Henderson Contextual guidance of eye movements and attention in real-world scenes: the role of global features on object search Psychological Review 113 October (4) 2006 766 786
19. A. Garcia-Diaz et al., Saliency based on decorrelation and distinctiveness of local responses, in: Proceedings of 13th International Conference on Computer Analysis of Images and Patterns, 2009, pp. 261-268.
20. A. Garcia-Diaz, et al., Decorrelation and distinctiveness provide with human-like saliency, in: J. Blanc-Talon, et al., (Eds.), Proceedings of 11th International Conference on Advanced Concepts for Intelligent Vision Systems, 2009, pp. 343-354.
21. Ayellet Tal Stas Goferman, Lihi Zelnik-Manor, Context-aware saliency detection, in: IEEE Conference on Computer Vision and Pattern Recognition, 2010.
22. B. Schauerte, G.A. Fink, Focusing computational visual attention in multi-modal human-robot interaction, in: International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction, ACM, 2010, p. 6.
23. X. Hou, L. Zhang, Saliency detection: a spectral residual approach, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007.
24. C. Kanan Sun: top-down saliency using natural statistics Visual Cognition 17 6/7 2009 979 1003
25. L. Zhang Sun A Bayesian framework for saliency using natural statistics Journal of Vision 8 7 2008 1 20
26. F. Estrada R. Achanta, S. Hemami, S. Susstrunk, Frequency-tuned salient region detection, in: IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2009.
27. Jian Li, et al., Saliency detection based on frequency and spatial domain analyses, in: Jesse Hoey, Stephen McKenna, Emanuele Trucco (Eds.), Proceedings of the British Machine Vision Conference, 2011, pp. 86.1-86.11.
28. B. Schauerte, R. Stiefelhagen, Predicting human gaze using quaternion dct image signature saliency and face detection, in: Proceedings of the 12th IEEE Workshop on the Applications of Computer Vision (WACV)/IEEE Winter Vision Meetings, Breckenridge, January 2012, pp. 9-11.
29. J.G. Daugman Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters Journal of the Optical Society of America 2 July (7) 1985 1160 1169
30. L. Itti, and C. Koch Comparaison of feature combination strategies for saliency-based visual attention systems SPIE Human Vision and Electronic Imaging (HVEI'99) 3644 1999 473 482
31. M. Mancas Relative influence of bottom-up and top-down attention Attention in Cognitive Systems 2009 212 226
32. N. Riche, M. Mancas, B. Gosselin, T. Dutoit, Rare: a new bottom-up saliency model, in: Proceedings of the IEEE International Conference of Image Processing (ICIP), 2012.
33. Gert Kootstra, Bart de Boer, and Lambert Schomaker Predicting eye fixations on complex visual stimuli using local symmetry Cognitive Computation 3 1 2011 223 240
34. D. Green, and J. Swets Signal Detection Theory and Psychophysics 1966 John Wiley New York
35. L. Itti, R.J. Peters, A. Iyer, and C. Koch Components of bottom-up gaze allocation in natural images Vision Research 45 18 2005 2397 2416
36. J.M. Henderson Visual saliency does not account for eye movements during visual search in real-world scenes Eye Movements: A Window on Mind and Brain 2007 537 562
37. Olivier Le Meur, and Thierry Baccino Methods for comparing scanpaths and saliency maps: strengths and weaknesses Behavior Research Methods 2012 1 16
38. Qi Zhao, and Christof Koch Learning a saliency map using fixated locations in natural scenes Journal of Vision 11 2011 1 15
39. Ali Borji, et al., Quantitative analysis of human-model agreement in visual saliency modeling: a comparative study, in: IEEE Transactions on Image Processing, in press.
40. Ali Borji, Evaluation measures for saliency maps: AUROC and NSS. https://sites.google.com/site/saliencyevaluation/evaluation-measures.
41. F. Sawyer Steven, Analysis of variance: The fundamental concepts, The Journal of Manual and Manipulative Therapy, 17 (2) (2009) 27E-38E.
42. David C. Howell Statistical Methods for Psychology (Psy 613 Qualitative Research and Analysis in Psychology) 2012 Wadsworth Publishing
43. Barbara G. Tabachnick, and Linda S. Fidell Using Multivariate Statistics 6th ed. 2012 Prentice Hall
44. H. Hentschke, M.C. Stüttgen, Computation of measures of effect size for neuroscience data sets, European Journal of Neuroscience, 2011.
45. Jacob Cohen Statistical Power Analysis for the Behavioral Sciences 2nd ed. 1988 Routledge Academic
46. Mark W. Lipsey Design Sensitivity: Statistical Power for Experimental Research (Applied Social Research Methods) 1989 Sage Publications Inc.