Salient region detection using high level feature

In the last few decades, selective visual attention has been extensively studied for its promising contributions to computer vision applications. Many different models have been proposed to compute visual saliency, which can be coarsely formulated as computational or psychophysical. Most existing methods are based on bottom-up mechanism, an automatic human behavior to guide gaze allocation. And low level features such as color, intensity and orientation are commonly adopted to compute saliency map. In this work, we propose a saliency computation method that integrates high-level information of object with low-level features. The result map is more suitable for most top-down tasks in the field of mobile robot requiring object information.

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

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

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

[4]  Gabriela Csurka,et al.  A framework for visual saliency detection with applications to image thumbnailing , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[5]  C. Koch,et al.  Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.

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

[7]  Liang-Tien Chia,et al.  Adaptive local context suppression of multiple cues for salient visual attention detection , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[8]  Liang-Tien Chia,et al.  Region-Based Saliency Detection and Its Application in Object Recognition , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[9]  David A. Clausi,et al.  Designing Gabor filters for optimal texture separability , 2000, Pattern Recognit..

[10]  S Ullman,et al.  Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.

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

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

[13]  Thomas Deselaers,et al.  What is an object? , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[14]  Tao Xiang,et al.  Looking Beyond the Image: Unsupervised Learning for Object Saliency and Detection , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[15]  Wilson S. Geisler,et al.  Multichannel Texture Analysis Using Localized Spatial Filters , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Tieniu Tan,et al.  Invariant texture segmentation via circular Gabor filters , 2002, Object recognition supported by user interaction for service robots.

[17]  Robert B. Fisher,et al.  Object-based visual attention for computer vision , 2003, Artif. Intell..

[18]  Qi Tian,et al.  Saliency Density Maximization for Efficient Visual Objects Discovery , 2011, IEEE Transactions on Circuits and Systems for Video Technology.

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

[20]  Kristina J. Nielsen,et al.  Object features used by humans and monkeys to identify rotated shapes. , 2008, Journal of vision.

[21]  E. Bartha,et al.  Altered lymphocyte acetylcholinesterase activity in patients with senile dementia , 1987, Neuroscience Letters.

[22]  A J Schofield,et al.  What Does Second-Order Vision See in an Image? , 2000, Perception.

[23]  David A. McAllester,et al.  Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  John K. Tsotsos,et al.  Saliency, attention, and visual search: an information theoretic approach. , 2009, Journal of vision.

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

[26]  Anne Treisman,et al.  Features and objects in visual processing , 1986 .

[27]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

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

[29]  Thomas Deselaers,et al.  Measuring the Objectness of Image Windows , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[30]  P. Perona,et al.  Objects predict fixations better than early saliency. , 2008, Journal of vision.

[31]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  Matthew B. Blaschko,et al.  Learning a category independent object detection cascade , 2011, 2011 International Conference on Computer Vision.

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

[34]  Laurent Itti,et al.  Interesting objects are visually salient. , 2008, Journal of vision.

[35]  B. Julesz,et al.  Texton gradients: The texton theory revisited , 2004, Biological Cybernetics.

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