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Identical-video retrieval using the low-peak feature of a video's audio information

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Journal of Zhejiang University-Science C(Computers and Electronics) 2010年第3期11卷 151-159页

作者： Myoung-beom CHUNG Il-ju KO Department of Media Soongsil University

The recognition and retrieval of identical videos by combing through entire video files requires a great deal of time and memory space. Therefore, most current video-matching methods analyze only a part of each video's image frame information. All these methods, however, share the critical problem of erroneously categorizing identical videos as different if they have merely been altered in resolution or converted with a different codec. This paper deals instead with an identical-video-retrieval method using the low-peak feature of audio data. The low-peak feature remains relatively stable even with changes in bit-rate or codec. The proposed method showed a search success rate of 93.7% in a video matching experiment. This approach could provide a technique for recognizing identical content on video file share sites.

关键词： video retrieval video DNA Audio signal processing Audio feature extraction

Semantics in Image and video retrieval Systems

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The Journal of China Universities of Posts and Telecommunications 2002年第4期9卷 57-63页

作者： CAIJun LIXiao-fei LabofMultimediaCommunications DepartmentofInformationEngineeringNanjingUniversityofPostsandTelecommunicationsNanjing210003P.R.China LabofMultimediaCommunications DepartmentofInformationEngineering

Multimedia document annotation is used in traditional multimedia databasesystems. However, without the help of human beings, it is very difficult to extract the semanticcontent of multimedia automatically. On the other hand, it is a tedious job to annotate multimediadocuments in large databases one by one manually. This paper first introduces a method to constructa semantic net-work on top of a multimedia database. Second, a useful and efficient annotationstrategy is presented based on the framework to obtain an accurate and rapid annotation of anymultimedia databases. Third, two methods of joint similarity measures for semantic and low-levelfeatures are evaluated .

关键词： image retrieval video retrieval semantic-based information retrieval MPEG-7 content-based feature semantics

High-level representation sketch for video event retrieval

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Science China(Information Sciences) 2016年第7期59卷 158-172页

作者： Yu ZHANG Xiaowu CHEN Liang LIN Changqun XIA Dongqing ZOU State Key Laboratory of Virtual Reality Technology and Systems School of Compute Science and EngineeringBeihang University School of Advanced Computing Sun Yat-Sen University

Representing video events is an essential step for a wide range of visual applications. In this paper,we propose the event sketch, a high-level event representation, to depict the dynamic properties of video events composed of actions of semantic objects. We show that this representation can facilitate a novel sketch based video retrieval(SBVR) system, which has not been considered before to the best of our knowledge. In this system, users are allowed to draw the evolutions(e.g. spatiotemporal layouts and behaviors of semantic objects)on a board, and retrieve the events whose semantic objects have the similar evolutions from a database. To do this, event sketches are constructed on both the user queries and database videos, and compared under a novel graph-matching scheme based on data-driven Monta Carlo Markov chain(DDMCMC). To test our approach, we collect a novel dataset of goal events in real soccer videos, which consists actions of multiple players and shows large variability in the evolution process of the events. Experiments on this dataset and the publicly available dataset CAVIAR demonstrated the effectiveness of the proposed approach.

关键词： video retrieval event representation event sketch drawing board distance function relevance feedback DDMCMC

Semantic and Structural Analysis of TV Diving Programs

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Journal of Computer Science & Technology 2004年第6期19卷 928-935页

作者： FeiWang Jin-TaoLi Yong-DongZhang Shou-XunLin InstituteofComputingTechnology TheChineseAcademyofSciencesBeijing100080P.R.China

Automatic content analysis of sports videos is a valuable and challenging task. Motivated by analogies between a class of sports videos and languages, the authors propose a novel approach for sports video analysis based on compiler principles. It integrates both semantic analysis and syntactic analysis to automatically create an index and a table of contents for a sports video. Each shot of the video sequence is first annotated and indexed with semantic labels through detection of events using domain knowledge. A grammar-based parser is then constructed to identify the tree structure of the video content based on the labels. Meanwhile, the grammar can be used to detect and recover errors during the analysis. As a case study, a sports video parsing system is presented in the particular domain of diving. Experimental results indicate the proposed approach is effective. Keywords sports video - event detection - grammar - video retrieval - content analysis and index This work was supported in part by the State Physical Culture Administration of China under Grant No.02005.Fei Wang was born in 1977. He is a Ph.D. candidate at Institute of Computing Technology (ICT), the Chinese Academy of Sciences (CAS). He received the B.S. degree in electrical engineering from Zhejiang University in 1999 and the M.S degree in computer science from Graduate School of the Chinese Academy of Sciences in 2001. His current research interests include content-based video analysis and retrieval.Jin-Tao Li was born in 1962. He is a professor and Ph.D. supervisor at ICT, CAS. His main research areas include multimedia data compression, virtual reality, and home network.Yong-Dong Zhang was born in 1973. He is an associate professor at ICT, CAS. His main research areas include multimedia data compression and multimedia information retrieval.Shou-Xun Lin was born in 1948. He is a professor and Ph.D. supervisor at ICT, CAS. His main research areas include multimedia technology and system

关键词： sports video event detection grammar video retrieval content analysis and index

video Key Frame Extraction by Unsupervised Clustering and Feedback Adjustment

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Journal of Computer Science & Technology 1999年第3期14卷 283-288,F003页

作者：庄越挺芮勇等 DepartmentofComputerScience ZhejingUniversityHangzhou310027PR.China BeckmanInstitute UniversityofI

In video information retrieval, key frame extraction has been rec ognized as one of the important research issues. Although much progress has been made, the existing approaches are either computationally expensive or ineffective in capturing salient visual content. In this paper, we first discuss the importance of key frame extraction and then briefly review and evaluate the existing approaches. To overcome the shortcomings of the existing approaches, we introduce a new algorithm for key frame extraction based on unsupervised clustering. Meanwhile, we provide a feedback chain to adjust the granularity of the extraction result. The proposed algorithm is both computationally simple and able to capture the visual *** efficiency and effectiveness are validated by large amount of real-world videos.

关键词： key frame extraction clustering feedback video retrieval

A temporal context model for boosting video annotation

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Science China(Information Sciences) 2013年第11期56卷 92-105页

作者： YI Jian PENG YuXin XIAO JianGuo Institute of Computer Science and Technology Peking University

In this paper,we propose a new method to model the temporal context for boosting video annotation *** motivation of our idea mainly comes from the fact that temporally continuous shots in video are generally with relevant content,so that the performance of video annotation could be comparably boosted by mining the temporal dependency between shots in *** on this consideration,we propose a temporal context model to mine the redundant information between *** connecting our model with conditional random feld and borrowing the learning and inference approaches from it,we could obtain the refned probability of a concept occurring in the shot,which is the leverage of temporal context information and initial output of video *** with existing methods for temporal context mining of video annotation,our model could capture diferent kinds of shot dependency more accurately to improve the video annotation ***,our model is relatively simple and efcient,which is important for the applications which have large scale data to *** experimental results on the widely used TRECVID datasets exhibit the efectiveness of our method for improving video annotation accuracy.

关键词： video annotation temporal context conditional random feld video retrieval

Key Frame Extraction Using Unsupervised Clustering Based on a Statistical Model

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Tsinghua Science and Technology 2005年第2期10卷 169-173页

作者：阳书平林行刚 Department of Electronic Engineering Tsinghua University Beijing 100084 China

This paper proposes a novel algorithm for extracting key frames to represent video shots. Re- garding whether, or how well, a key frame represents a shot, different interpretations have been suggested. We develop our algorithm on the assumption that more important content may demand more attention and may last relatively more frames. Unsupervised clustering is used to divide the frames into clusters within a shot, and then a key frame is selected from each candidate cluster. To make the algorithm independent of video sequences, we employ a statistical model to calculate the clustering threshold. The proposed algo- rithm can capture the important yet salient content as the key frame. Its robustness and adaptability are validated by experiments with various kinds of video sequences.

关键词： key frame video retrieval motion compensation

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一种基于运动轨迹的视频检索方法

一种基于运动轨迹的视频检索方法