Saliency Detection via Foreground and Background Seeds

In this paper, we come up with a bottom-up saliency algorithm that both consider the background and foreground cues. First, we compute the coarse saliency map by manifold ranking on a graph using partly image boundaries which consider as background prior. In this step, we just select left and top sides as background seeds. Second, bi-segment the preliminary saliency map to extract foreground information. Third, we utilize Markov absorption probabilities to highlight objects against the background. Results on public datasets show that our proposed method achieve fabulous performance.

[1]  Jian Sun,et al.  Saliency Optimization from Robust Background Detection , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[2]  Ronen Basri,et al.  Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

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

[4]  Huchuan Lu,et al.  Salient object detection via bootstrap learning , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Huchuan Lu,et al.  Saliency Detection via Graph-Based Manifold Ranking , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

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

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

[8]  Shang-Hong Lai,et al.  Fusing generic objectness and visual saliency for salient object detection , 2011, 2011 International Conference on Computer Vision.

[9]  Pietro Perona,et al.  Is bottom-up attention useful for object recognition? , 2004, CVPR 2004.

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

[11]  Lihi Zelnik-Manor,et al.  What Makes a Patch Distinct? , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Sheldon M. Ross.  Introduction to Probability Models. , 1995 .

[13]  Huchuan Lu,et al.  Inner and Inter Label Propagation: Salient Object Detection in the Wild , 2015, IEEE Transactions on Image Processing.

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

[15]  Tim K Marks,et al.  SUN: A Bayesian framework for saliency using natural statistics. , 2008, Journal of vision.

[16]  Huchuan Lu,et al.  Saliency Detection via Dense and Sparse Reconstruction , 2013, 2013 IEEE International Conference on Computer Vision.

[17]  Li Xu,et al.  Hierarchical Saliency Detection , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[18]  Wei-Ying Ma,et al.  Data-driven approach for bridging the cognitive gap in image retrieval , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).

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

[20]  Vibhav Vineet,et al.  Efficient Salient Region Detection with Soft Image Abstraction , 2013, 2013 IEEE International Conference on Computer Vision.

[21]  Ming-Hsuan Yang,et al.  Top-down visual saliency via joint CRF and dictionary learning , 2012, CVPR.

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

[23]  Huchuan Lu,et al.  Saliency Region Detection Based on Markov Absorption Probabilities , 2015, IEEE Transactions on Image Processing.

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

[25]  Deepu Rajan,et al.  Random Walks on Graphs for Salient Object Detection in Images , 2010, IEEE Transactions on Image Processing.

[26]  Huchuan Lu,et al.  Bayesian Saliency via Low and mid Level Cues , 2022 .

[27]  Weisi Lin,et al.  Saliency Detection in the Compressed Domain for Adaptive Image Retargeting , 2012, IEEE Transactions on Image Processing.

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

[29]  Huchuan Lu,et al.  Saliency Detection with Multi-Scale Superpixels , 2014, IEEE Signal Processing Letters.

[30]  Andrea Vedaldi,et al.  Objects in Context , 2007, 2007 IEEE 11th International Conference on Computer Vision.

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