Top down saliency estimation via superpixel-based discriminative dictionaries

BMVC 2014 - Proceedings of the British Machine Vision Conference 2014

Volumn , Issue , 2014, Pages

  Kocak, Aysun ^a   Cizmeciler, Kemal ^a   Erdem, Aykut ^a   Erdem, Erkut ^a  

^a HACETTEPE UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

ARTS COMPUTING; IMAGE SEGMENTATION; OBJECT RECOGNITION; RANDOM PROCESSES; VISUALIZATION;

CLASS-SPECIFIC DICTIONARIES; COMPLEX SCENES; CONDITIONAL RANDOM FIELD; DISCRIMINATIVE DICTIONARIES; OBJECT LOCALIZATION; STATE OF THE ART; TARGET OBJECT; VISUAL SALIENCY;

SUPERPIXELS;

EID: 85055087512     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/c.28.73     Document Type: Conference Paper

References (39)

1. R. Achanta and S. Susstrunk. Saliency detection for content-aware image resizing. In ICIP, pages 1005-1008, 2009.
2. R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Susstrunk. SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intell., 34(11):2274-2282, 2012.
3. D. Aldavert, A. Ramisa, R.L. de Mantaras, and R. Toledo. Fast and robust object segmentation with the integral linear classifier. In CVPR, pages 1046-1053, 2010.
4. B. Alexe, T. Deselares, and V. Ferrari. What is an object? In CVPR, 2010.
5. A. Borji and L. Itti. State-of-the-art in visual attention modeling. IEEE Trans. Pattern Anal. Mach. Intell., 35(1):185-207, 2013.
6. A. Borji, D. N. Sihite, and L. Itti. Salient object detection: A benchmark. In ECCV, pages 414-429, 2012.
7. N.J. Butko, Lingyun Zhang, G.W. Cottrell, and Javier R. Movellan. Visual saliency model for robot cameras. In ICRA, pages 2398-2403, 2008.
8. J. Carreira and C. Sminchisescu. Constrained parametric min-cuts for automatic object segmentation. In CVPR, 2010.
9. M.-M. Cheng, Z. Zhang,W.-Y. Lin, and P. Torr. BING: Binarized normed gradients for objectness estimation at 300fps. In CVPR, 2014.
10. R. G. Cinbis, J. Verbeek, and C. Schmid. Segmentation driven object detection with fisher vectors. In ICCV, 2013.
11. M. Donoser, M. Urschler, M. Hirzer, and H. Bischof. Saliency driven total variation segmentation. In ICCV, pages 817-824, 2009.
12. K. A. Ehinger, B. Hidalgo-Sotelo, A. Torralba, and A. Oliva. Modeling search for people in 900 scenes: A combined source model of eye guidance. Visual Cognition, 17 (6-7):945-978, 2009.
13. I. Endres and D. Hoiem. Category independent object proposals. In ECCV, 2010.
14. E. Erdem and A. Erdem. Visual saliency estimation by nonlinearly integrating features using region covariances. Journal of Vision, 13(4):1-20, 2013.
15. M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman. The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results. http://www.pascalnetwork.org/challenges/VOC/voc2007/workshop/index.html.
16. B. Fulkerson, A. Vedaldi, and S. Soatto. Class segmentation and object localization with superpixel neighborhoods. In ICCV, pages 670-677, 2009.
17. X. Hong, H. Chang, S. Shan, X. Chen, and W. Gao. Sigma set: A small second order statistical region descriptor. In CVPR, pages 1802-1809, 2009.
18. L. Itti. Automatic foveation for video compression using a neurobiological model of visual attention. IEEE Trans. Image Process., 13(10):1304-1318, 2004.
19. C. Kanan, M. H. Tong, L. Zhang, and G. W. Cottrell. SUN: Top-down saliency using natural statistics. Visual Cognition, 17(6-7):979-1003, 2009.
20. N. Khan and M.F. Tappen. Discriminative dictionary learning with spatial priors. In ICIP, pages 166-170, 2013.
21. Y.-F. Ma, X.-S. Hua, L. Lu, and H.-J. Zhang. A generic framework of user attention model and its application in video summarization. IEEE Trans. Mult., 7(5):907-919, 2005.
22. S. Manen, M. Guillaumin, and L. V. Gool. Prime object proposals with randomized Prim's algorithm. In ICCV, 2013.
23. R. Margolin, A. Tal, and Zelnik-Manori L. What makes a patch distinct? In CVPR, 2009.
24. M. Marszalek and C. Schmid. Accurate object recognition with shape masks. Int. J. Comput. Vision, 97(2):191-209, 2012.
25. V. Navalpakkam and L. Itti. An integrated model of top-down and bottom-up attention for optimizing detection speed. In CVPR, volume 2, pages 2049-2056, 2006.
26. A. Opelt, A. Pinz, M. Fussenegger, and P. Auer. Generic object recognition with boosting. IEEE Trans. Pattern Anal. Mach. Intell., 28(3):416-431, 2006.
27. F. Perazzi, P. Krähenbühl, Y. Pritch, and A. Hornung. Saliency filters: Contrast based filtering for salient region detection. In CVPR, pages 733-740, 2012.
28. E. Rahtu, J. Kannala, and M. Blaschko. Learning a category independent object detection cascade. In ICCV, 2011.
29. P. Rantalankila, J. Kannala, and E. Rahtu. Generating object segmentation proposals using global and local search. In CVPR, 2014.
30. C. Rother, V. Kolmogorov, and A. Blake. GrabCut: Interactive foreground extraction using iterated graph cuts. ACM Trans. Graph., 23(3):309-314, 2004.
31. U. Rutishauser, D. Walther, C. Koch, and P. Perona. Is bottom-up attention useful for object recognition? In CVPR, volume 2, pages II-37-II-44 Vol.2, June 2004.
32. G. Sharma, F. Jurie, and C. Schmid. Discriminative spatial saliency for image classification. In CVPR, pages 733-740, 2012.
33. C. Siagian and L. Itti. Rapid biologically-inspired scene classification using features shared with visual attention. IEEE Trans. Pattern Anal. Mach. Intell., 29(2):300-312, 2007.
34. A. Torralba, A Oliva, M.S. Castelhano, and J.M. Henderson. Contextual guidance of eye movements and attention in real-world scenes: The role of global features in object search. Psychological Review, 113(4):766-786, 2006.
35. O. Tuzel, F. Porikli, and P. Meer. Region covariance: A fast descriptor for detection and classification. ECCV, pages 589-600, 2006.
36. K. E. van de Sande, J. R. Uijlings, T. Gevers, and A. W. Smeulders. Segmentation as selective search for object recognition. In ICCV, 2011.
37. D. Walther and C. Koch. Modeling attention to salient proto-objects. Neural Netw., 19 (9):1395-1407, 2006.
38. C. Yang, L. Zhang, H. Lu, X. Ruan, and M.-H. Yang. Saliency detection via graphbased manifold ranking. In CVPR, pages 3166-3173, 2013.
39. J. Yang and M.-H. Yang. Top-down visual saliency via joint CRF and dictionary learning. In CVPR, pages 2296-2303, 2012.