Saliency Detection via Absorbing Markov Chain With Learnt Transition Probability

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Lihe Zhang Xiukui Li

Abstract

In this paper, we propose a bottom-up saliency model based on absorbing Markov chain (AMC). First, a sparsely connected graph is constructed to capture the local context information of each node. All image boundary nodes and other nodes are, respectively, treated as the absorbing nodes and transient nodes in the absorbing Markov chain. Then, the expected number of times from each transient node to all other transient nodes can be used to represent the saliency value of this node. The absorbed time depends on the weights on the path and their spatial coordinates, which are completely encoded in the transition probability matrix. Considering the importance of this matrix, we adopt different hierarchies of deep features extracted from fully convolutional networks and learn a transition probability matrix, which is called learnt transition probability matrix. Although the performance is significantly promoted, salient objects are not uniformly highlighted very well. To solve this problem, an angular embedding technique is investigated to refine the saliency results. Based on pairwise local orderings, which are produced by the saliency maps of AMC and boundary maps, we rearrange the global orderings (saliency value) of all nodes. Ex...Continue Reading

References

Nov 17, 2010·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Viswanath GopalakrishnanDeepu Rajan
Jan 5, 2011·IEEE Transactions on Pattern Analysis and Machine Intelligence·Tie LiuHeung-Yeung Shum
May 18, 2011·IEEE Transactions on Pattern Analysis and Machine Intelligence·Stella Yu
Sep 29, 2011·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Congyan LangShuicheng Yan
Sep 8, 2012·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Yulin XieMing-Hsuan Yang
Feb 24, 2015·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Jingang SunXiuping Liu
Sep 10, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Ming-Ming ChengShi-Min Hu

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Citations

Jul 10, 2019·Journal of X-ray Science and Technology·Xiaoling TangJiangli Lin
Jan 24, 2019·Sensors·Mian Muhammad Sadiq FareedMuhammad Zeeshan Fareed
Dec 9, 2020·Entropy·Ashish Kumar GuptaPritee Khanna
Jun 12, 2021·Neural Networks : the Official Journal of the International Neural Network Society·Ying Ying ZhangPing Zhang

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