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visual summarization of image collections by fast RANSAC

NEUROCOMPUTING 2016年 172卷 48-52页

作者： Zhao, Ye Hong, Richang Jiang, Jianguo Hefei Univ Technol Sch Comp & Informat Hefei 230009 Peoples R China

In this paper we propose a novel approach to select a summary set of images from a large image collection by improved Random Sample Consensus (RANSAC) and Affinity Propagation (AP) clustering. It can automatically select a small set of representatives to highlight all the significant visual properties of a given image collection. The proposed framework mainly composes four stages. First, the scale-invariant feature of each image is extracted by Scale Invariant Feature Transform (SIFT). Second, keypoints of two images are matched and ranked based on nearest neighbor ratio. The representative dataset of RANSAC is established by a minimal number of optimal matches. Third, the target homographic matrix is fitted based on the representative dataset Mismatches are filtered out via the homographic matrix. Finally, summarization is automatically formulated as an optimization framework by AP clustering. We conduct experiments on a set of Paris which is consisting of 1000 images downloaded from Flickr. The results show that the proposed approach significantly outperforms other methods. (C) 2015 Elsevier B.V. All rights reserved.

关键词： visual summarization Random sample consensus Affinity propagation Nearest neighbor distance search

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visual summarization OF LANDMARKS VIA VIEWPOINT MODELING

VISUAL SUMMARIZATION OF LANDMARKS VIA VIEWPOINT MODELING

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19th IEEE International Conference on Image Processing (ICIP)

作者： Xue, Yao Qian, Xueming Xi An Jiao Tong Univ Xian 710049 Peoples R China

ISBN: (纸本)9781467325332;9781467325349

In this paper, we describe an approach for visually summarizing a landmark by recommending images with diverse viewpoints (e. g. front-side viewpoint, bottom-top viewpoint, close-distant viewpoint, etc). Our approach models an image's viewpoint using a 4-D viewpoint vector, which describes viewpoint in horizontal, vertical, scale and orientation aspects. To construct the viewpoint vector for an image, we select Identical Semantic Points (ISPs) from hundreds to thousands SIFT points of the image to captures some major and unique parts of a landmark. Then a four dimensional viewpoint vector is utilized to measure on the position coordinate, scale and orientation of the ISPs in an image. After that, we perform viewpoint clustering to finally summarize landmarks. We evaluate our approach on 5K Oxford building image set and provide final summarization results for some famous landmarks in Oxford.

关键词： visual summarization Viewpoint Modeling Identical Semantic Points SIFT

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visual summarization of Web Pages

Visual Summarization of Web Pages

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33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

作者： Jiao, Binxing Yang, Linjun Xu, Jizheng Wu, Feng Univ Sci & Technol China MOE MS KeyLab MCC Hefei 230026 Peoples R China

ISBN: (纸本)9781605588964

visual summarization is an attractive new scheme to summarize web pages, which can help achieve a more friendly user experience in search and re-finding tasks by allowing users quickly get the idea of what the web page is about and helping users recall the visited web page. In this paper, we perform a careful study on the recently proposed visual summarization approaches, including the thumbnail of the web page snapshot, the internal image in the web page which is representative of the content in the page, and the visual snippet which is a synthesized image based on the internal image, the title, and the logo found in the web page. Moreover, since the internal image based summarization approach hardly works when the representative internal images are unavailable, we propose a new strategy, which retrieves the representative image from the external to summarize the web page. The experimental results suggest that the various summarization approaches have respective advantages on different types of web pages. While internal images and thumbnails can provide a reliable summarization on web pages with dominant images and web pages with simple structure respectively, the external images are regarded as a useful information to complement the internal images and are demonstrated very useful in helping users understanding new web pages. The visual snippet performs well on the re-finding tasks since it incorporates the title and logo which are advantageous on identifying the visited web pages.

关键词： web page summarization visual summarization

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EmotionCues: Emotion-Oriented visual summarization of Classroom Videos

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2021年第7期27卷 3168-3181页

作者： Zeng, Haipeng Shu, Xinhuan Wang, Yanbang Wang, Yong Zhang, Liguo Pong, Ting-Chuen Qu, Huamin Hong Kong Univ Sci & Technol Hong Kong Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Peoples R China Harbin Engn Univ Coll Comp Sci & Technol Harbin 150001 Peoples R China

Analyzing students' emotions from classroom videos can help both teachers and parents quickly know the engagement of students in class. The availability of high-definition cameras creates opportunities to record class scenes. However, watching videos is time-consuming, and it is challenging to gain a quick overview of the emotion distribution and find abnormal emotions. In this article, we propose EmotionCues, a visual analytics system to easily analyze classroom videos from the perspective of emotion summary and detailed analysis, which integrates emotion recognition algorithms with visualizations. It consists of three coordinated views: a summary view depicting the overall emotions and their dynamic evolution, a character view presenting the detailed emotion status of an individual, and a video view enhancing the video analysis with further details. Considering the possible inaccuracy of emotion recognition, we also explore several factors affecting the emotion analysis, such as face size and occlusion. They provide hints for inferring the possible inaccuracy and the corresponding reasons. Two use cases and interviews with end users and domain experts are conducted to show that the proposed system could be useful and effective for analyzing emotions in the classroom videos.

关键词： Videos Data visualization visualization Emotion recognition Uncertainty Face Computer vision Emotion classroom videos visual summarization visual analytics

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Episogram: visual summarization of Egocentric Social Interactions

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IEEE COMPUTER GRAPHICS AND APPLICATIONS 2016年第5期36卷 72-81页

作者： Cao, Nan Lin, Yu-Ru Du, Fan Wang, Dashun Tongji Univ Coll Design & Innovat Shanghai Peoples R China Univ Pittsburgh Sch Informat Sci Pittsburgh PA 15260 USA Univ Maryland Comp Sci College Pk MD USA Northwestern Univ Kellogg Sch Management Evanston IL 60208 USA

The key challenges of visualizing social interaction data include the difficulties of understanding the general structure of social interactions and representing the data in the context of various user activities to reveal different behavior patterns. The design of the proposed interactive visualization tool Episogram is based on an anatomy of social interaction process in which the actors and objects involved can be formally represented as a time-varying tripartite network. The authors show the effectiveness of the proposed technique using real-world datasets and user studies. [ABSTRACT FROM AUTHOR]

关键词： Behaviorial sciences computer graphics Data models Data visualization Electronic mail information visualization Shape analysis social interactions social media visualization Social network services Twitter visual summarization

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Interactive browsing via diversified visual summarization for image search results

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MULTIMEDIA SYSTEMS 2011年第5期17卷 379-391页

作者： Wang, Jingdong Jia, Liyan Hua, Xian-Sheng Beijing China

Presenting and browsing image search results play key roles in helping users to find desired images from search results. Most existing commercial image search engines present them, dependent on a ranked list. However, such a scheme suffers from at least two drawbacks: inconvenience for consumers to get an overview of the whole result, and high computation cost to find desired images from the list. In this paper, we introduce a novel search result summarization approach and exploit this approach to further propose an interactive browsing scheme. The main contribution of this paper includes: (1) a dynamic absorbing random walk to find diversified representatives for image search result summarization;(2) a local scaled visual similarity evaluation scheme between two images through inspecting the relation between each image and other images;and (3) an interactive browsing scheme, based on a tree structure for organizing the images obtained from the summarization approach, to enable users to intuitively and conveniently browse the image search results. Quantitative experimental results and user study demonstrate the effectiveness of the proposed summarization and browsing approaches.

关键词： visual summarization visual diversity Interactive browsing Image search results

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Content-Based visual summarization for Image Collections

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2021年第4期27卷 2298-2312页

作者： Pan, Xingjia Tang, Fan Dong, Weiming Ma, Chongyang Meng, Yiping Huang, Feiyue Lee, Tong-Yee Xu, Changsheng Chinese Acad Sci Inst Automat NLPR Beijing 100864 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Fosafer Beijing 100142 Peoples R China Kuaishou Technol Beijing 100085 Peoples R China Didi Chuxing Beijing 100000 Peoples R China Tencent YouTu Lab Shanghai 200233 Peoples R China Natl Cheng Kung Univ 34912 Tainan 701 Taiwan

With the surge of images in the information era, people demand an effective and accurate way to access meaningful visual information. Accordingly, effective and accurate communication of information has become indispensable. In this article, we propose a content-based approach that automatically generates a clear and informative visual summarization based on design principles and cognitive psychology to represent image collections. We first introduce a novel method to make representative and nonredundant summarizations of image collections, thereby ensuring data cleanliness and emphasizing important information. Then, we propose a tree-based algorithm with a two-step optimization strategy to generate the final layout that operates as follows: (1) an initial layout is created by constructing a tree randomly based on the grouping results of the input image set;(2) the layout is refined through a coarse adjustment in a greedy manner, followed by gradient back propagation drawing on the training procedure of neural networks. We demonstrate the usefulness and effectiveness of our method via extensive experimental results and user studies. Our visual summarization algorithm can precisely and efficiently capture the main content of image collections better than alternative methods or commercial tools.

关键词： visualization Layout Correlation Backpropagation Optimization Computational modeling Semantics visual summarization photo collection collage layout tree-based algorithm gradient back propagation

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visual and Textual summarization of Webpages

Visual and Textual Summarization of Webpages

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International Conference on Data Mining and Intelligent Computing (ICDMIC)

作者： Akhtar, Nadeem Siddique, Bushra Afroz, Rounaque Aligarh Muslim Univ Dept Comp Engn Aligarh Uttar Pradesh India

ISBN: (纸本)9781479946747

Search and re-finding tasks are among the most typical applications on internet. In order to make these tasks more efficient, we propose an attractive new scheme to visually summarize web pages. This would allow users to quickly get the idea of what the webpage is all about and helping users to recall the visited web pages. For the purpose, we employ latent semantic analysis to prepare a gist of the textual contents accompanied by title and a relevant image. The image could be internal or external depending upon the contents of the webpage. If the webpage contains dominant internal images, ranking algorithm is employed to select the most dominant internal image for summarization. If not, key phrases are extracted from the textual part for the purpose of searching the entire internet for a relevant external image. After the image search results are obtained, re-ranking algorithm is applied to select the most appropriate image.

关键词： text summarization visual summarization

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Urban scene representation and summarization using knowledge graph

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 275卷

作者： Pandey, Sourav Patel, Ashish Singh Natl Inst Technol Mizoram Dept Comp Sci & Engn Aizawl 796012 Mizoram India

The rapid growth in the volume of visual data and its wide applications in real-world scene summarization is essential for enabling efficient and meaningful access to image or video content. Most existing methods are based on deep learning, have limitations in running time, accuracy, and resource constraints, and require intensive, which is often challenging in the case of video data. In addition, current technologies have limitations arising from the inability of existing systems to fully leverage the interdependence of entities and semantic relationships within a scene. Thus, this work proposes an approach that leverages contextual knowledge to enhance scene summarization for images and videos using a knowledge graph. The proposed approach integrates relationships, lateral, spatial, and cognitive aspects into a unified knowledge graph, creating visual relations between objects. In addition, the entities are integrated using a cognitive-label graph that incorporates lateral meaning and semantic relationships to generate descriptive text capturing the essence of a scene. Moreover, the cognitive graph generates potentially unidentified entities and relations within a scene. In addition, the proposed approach incorporates contextual cues, such as object interactions and scene layout, to distinguish objects beyond appearance. The proposed work is evaluated on a segment of the visual Genome and Udacity Self-Driving Car dataset, which has been modified to extract additional information for scene summarization. Furthermore, the proposed approach provides a comprehensive understanding of scenes, improving the accuracy and efficiency of generating informative text descriptions for applications like autonomous driving and visual perception.

关键词： Contextual knowledge Spatial information Cognitive graph Knowledge graph visual summarization

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Landmark summarization With Diverse Viewpoints

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2015年第11期25卷 1857-1869页

作者： Qian, Xueming Xue, Yao Yang, Xiyu Tang, Yuan Yan Hou, Xingsong Mei, Tao Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Peoples R China Macau Univ Fac Sci & Technol Macau Peoples R China Microsoft Res Beijing 100080 Peoples R China

Landmark summarization with diverse viewpoints is very important in landmark retrieval, as it can create a comprehensive description of a landmark for users. In this paper we present an approach for summarizing a collection of landmark images from diverse viewpoints. First, we group landmark images with content overlap by viewpoint album (VA) generation. Second, we model the relative viewpoint of each image within the VA based on the spatial layout of distinctive descriptors of a landmark. Third, we express the relative viewpoint of an image with a 4-D viewpoint vector, including horizontal, vertical, scale, and rotation. Finally, we summarize the landmarks in terms of viewpoints. Experimental results show the effectiveness of the proposed landmark summarization approach.

关键词： Geometric consistency check landmark retrieval viewpoint modeling visual summarization

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