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Automatic salient object sequence rebuilding for video segment analysis

Science China(Information Sciences) 2018年第1期61卷 249-260页

作者： Tie LIU Haibin DUAN Yuanyuan SHANG Zejian YUAN Nanning ZHENG School of Automation Science and Electrical Engineering Beihang University Information Engineering College Capital Normal University The School of Electronic and Information Engineering Xi'an Jiaotong University

Detection of salient object sequences from video data is challenging when the salient object changes between consecutive frames. In this study, we addressed the salient object sequence rebuilding problem with video segment analysis. We reformulated the problem as a binary labeling problem, analyzed the potential salient object sequences in the video using a clustering method, and separated the salient object sequence from the background by applying an energy optimization method. Our proposed approach determines whether temporal consecutive pixels belong to the same salient object sequence. The conditional random field is then learned to effectively integrate the salient features and the sequence consecutive constraints.A dynamic programming algorithm was developed to resolve the energy minimization problem *** results confirmed the ability of our approach to address the salient object rebuilding problem in automatic visual attention applications and video content analysis.

关键词： salient object video attention sequence segment analysis conditional random model

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Automatic salient object segmentation using saliency map and color segmentation

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Journal of Central South University 2013年第9期20卷 2407-2413页

作者： HAN Sung-ho JUNG Gye-dong LEE Sangh-yuk HONG Yeong-pyo LEE Sang-hun Department of Plasmabiodisplay Kwangwoon University Department of General Education Kwangwoon University Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Department of Hospital Management International University of Korea

A new method for automatic salient object segmentation is *** object segmentation is an important research area in the field of object recognition,image retrieval,image editing,scene reconstruction,and 2D/3D *** this work,salient object segmentation is performed using saliency map and color ***,color and intensity feature are extracted from mean shift segmentation(MSS)image,and saliency map is created using these *** average saliency per segment image is calculated using the color information from MSS image and generated saliency ***,second average saliency per segment image is calculated by applying same procedure for the first image to the thresholding,labeling,and hole-filling applied ***,labeling and hole-filling are applied to the mean image of the generated two images to get the final salient object *** effectiveness of proposed method is proved by showing 80%,89%and 80%of precision,recall and F-measure values from the generated salient object segmentation image and ground truth image.

关键词： salient object visual attention saliency map color segmentation

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salient object Detection Based on Background Model

Salient Object Detection Based on Background Model

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第37届中国控制会议

作者： Yanbang Zhang Fen Zhang Lei Guo College of Mathematics and Information Science Xianyang Normal University School of Automation Northwestern Polytechnical University Department of Automatic Control Xidian University

In this paper, we propose a novel bottom-up method for detecting salient object. First, a coarse saliency map is generated by according to the biggest symmetric surround model and the color distribution-based model. And then, we design a Gauss filter to enhance the coarse saliency map, and preliminarily establish the background model. Next, the salient feature is defined as the color contrast between background region and the rest. Extensive experiments show the performance of the proposed method which performs better in five evaluation indexes.

关键词： Computer vision object detection visual attention salient object bottom-up model

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