Hierarchical Saliency Detection

When dealing with objects with complex structures, saliency detection confronts a critical problem - namely that detection accuracy could be adversely affected if salient foreground or background in an image contains small-scale high-contrast patterns. This issue is common in natural images and forms a fundamental challenge for prior methods. We tackle it from a scale point of view and propose a multi-layer approach to analyze saliency cues. The final saliency map is produced in a hierarchical model. Different from varying patch sizes or downsizing images, our scale-based region handling is by finding saliency values optimally in a tree model. Our approach improves saliency detection on many images that cannot be handled well traditionally. A new dataset is also constructed.

[1]  A. Treisman,et al.  A feature-integration theory of attention , 1980, Cognitive Psychology.

[2]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  S. Palmer.  Vision Science : Photons to Phenomenology , 1999 .

[4]  Jitendra Malik,et al.  A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[5]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Christof Koch,et al.  Attentional Selection for Object Recognition - A Gentle Way , 2002, Biologically Motivated Computer Vision.

[7]  X. Jin.  Factor graphs and the Sum-Product Algorithm , 2002 .

[8]  C. Frith,et al.  Directing attention to locations and to sensory modalities: multiple levels of selective processing revealed with PET. , 2002, Cerebral cortex.

[9]  Tai Sing Lee,et al.  Hierarchical Bayesian inference in the visual cortex. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.

[10]  HongJiang Zhang,et al.  Contrast-based image attention analysis by using fuzzy growing , 2003, MULTIMEDIA '03.

[11]  Daniel P. Huttenlocher,et al.  Efficient Graph-Based Image Segmentation , 2004, International Journal of Computer Vision.

[12]  Jianguo Zhang,et al.  The PASCAL Visual Object Classes Challenge , 2006 .

[13]  Mubarak Shah,et al.  Visual attention detection in video sequences using spatiotemporal cues , 2006, MM '06.

[14]  Luc Van Gool,et al.  The 2005 PASCAL Visual Object Classes Challenge , 2005, MLCW.

[15]  Pietro Perona,et al.  Graph-Based Visual Saliency , 2006, NIPS.

[16]  Liqing Zhang,et al.  Saliency Detection: A Spectral Residual Approach , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[17]  Benjamin W Tatler,et al.  The central fixation bias in scene viewing: selecting an optimal viewing position independently of motor biases and image feature distributions. , 2007, Journal of vision.

[18]  Nanning Zheng,et al.  Learning to Detect a Salient Object , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  Sabine Süsstrunk,et al.  Salient Region Detection and Segmentation , 2008, ICVS.

[20]  S. HiremathP.,et al.  Content Based Image Retrieval using Color Boosted Salient Points and Shape features of an image , 2008 .

[21]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[22]  S. Süsstrunk,et al.  Frequency-tuned salient region detection , 2009, CVPR 2009.

[23]  Frédo Durand,et al.  Learning to predict where humans look , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[24]  Simone Frintrop,et al.  Center-surround divergence of feature statistics for salient object detection , 2011, 2011 International Conference on Computer Vision.

[25]  Shi-Min Hu,et al.  Global contrast based salient region detection , 2011, CVPR 2011.

[26]  Alexander Toet,et al.  Computational versus Psychophysical Bottom-Up Image Saliency: A Comparative Evaluation Study , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  Shang-Hong Lai,et al.  From co-saliency to co-segmentation: An efficient and fully unsupervised energy minimization model , 2011, CVPR 2011.

[28]  Yael Pritch,et al.  Saliency filters: Contrast based filtering for salient region detection , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[29]  Jian Sun,et al.  Geodesic Saliency Using Background Priors , 2012, ECCV.

[30]  Ying Wu,et al.  A unified approach to salient object detection via low rank matrix recovery , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[31]  Cordelia Schmid,et al.  Discriminative spatial saliency for image classification , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[32]  Lihi Zelnik-Manor,et al.  Context-Aware Saliency Detection , 2012, IEEE Trans. Pattern Anal. Mach. Intell..