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Extracting Objects and Events from MPEG Videos for Highlight-based Indexing and Retrieval

Jinchang Ren, Jianmin Jiang, Juan Chen, Stan S. Ipson
2010 Journal of Multimedia  
Video highlight high-level semantics are then automatically extracted via low-level analysis in the detection of human objects and camera motion events, and finally these highlights are taken for shot-level  ...  In this paper, we propose techniques to solve this problem using knowledge supported extraction of semantics, and compressed-domain processing is employed for efficiency.  ...  ACKNOWLEDGMENT This work was supported in part by grants from EU IST Framework Research Programme projects HERMES (IST-216709) and LIVE (IST-4-027312).  ... 
doi:10.4304/jmm.5.2.95-103 fatcat:3dfbgaovgzajzipb23p25rqdba

Survey on Video Big Data: Analysis Methods and Applications

P. Ushapreethi, G.G. Lakshmipriya
2017 International Journal of Applied Engineering Research  
This paper summarizes the description of the background to common approaches in visual content-based big video storage and retrieval.  ...  In this big data era, Video data face its new challenges to store and retrieve, since the size of video data is high and the processing and analysis methods are very complex.  ...  Due to these inconveniences of static features, the attraction towards motion features was increased in video analysis and the same is discussed in the next section Motion Features: Motion is the key feature  ... 
doi:10.37622/ijaer/12.10.2017.2221-2231 fatcat:ghhxte6fkfdipesh4osdlmj224


2001 International Journal of Image and Graphics  
In this paper, we present major issues in video parsing, abstraction, retrieval and semantic analysis. We discuss the success, the difficulties and the expectations in these areas.  ...  We then describe visual features, in particular motion, and similarity measures adopted for retrieval.  ...  Acknowledgments This work is supported in part by RGC Grants HKUST661/95E and HKUST6072/97E.  ... 
doi:10.1142/s0219467801000268 fatcat:aob23yerxvetnlvrye3nw6nfki

ICBR – Multimedia Management System for Intelligent Content Based Retrieval [chapter]

Janko Ćalić, Neill Campbell, Majid Mirmehdi, Barry T. Thomas, Ron Laborde, Sarah Porter, Nishan Canagarajah
2004 Lecture Notes in Computer Science  
Novel techniques will be applied to temporal analysis, intelligent key-frame extraction, animal gait analysis, semantic modelling and audio classification.  ...  Its objectives are founded on the integration of a large-scale wildlife digital media archive with a manually annotated semantic metadata organised in a structured taxonomy and media classification system  ...  Acknowledgements The work reported in this paper has formed part of the ICBR project within the 3C Research programme of convergent technology research for digital media processing and communications whose  ... 
doi:10.1007/978-3-540-27814-6_70 fatcat:blnfvc3ez5fgxdjcenol3ecky4

InsightVideo: toward hierarchical video content organization for efficient browsing, summarization and retrieval

Xingquan Zhu, A.K. Elmagarmid, Xiangyang Xue, Lide Wu, A.C. Catlin
2005 IEEE transactions on multimedia  
Xiangyang Xue received the B.S., M.S., and Ph.D. degrees in communication engineering from Xidian University,  ...  He is on the steering committees for the IEEE International Conference on Data Engineering, and the IEEE Symposium on Research Issues in Data Engineering and served on the organization committees of several  ...  Wu at the University of Vermont for his valuable comments in revising the paper.  ... 
doi:10.1109/tmm.2005.850977 fatcat:4zrpbh4jmzgjrja5vi6nid7bhu

Compressed domain video retrieval using object and global motion descriptors

R. Venkatesh Babu, K. R. Ramakrishnan
2006 Multimedia tools and applications  
In this paper we propose a system to extract the object-based and global features from compressed MPEG video using the motion vector information for video retrieval.  ...  The global features like motion activity and camera motion parameters are extracted from the above enhanced motion information.  ...  The authors have not come across any work that uses both global and object features extracted from compressed domain for video retrieval purpose. The limitations of  ... 
doi:10.1007/s11042-006-0048-9 fatcat:a7iwli4c65apvm7kyqmnldyy5u

Introduction to the special issue on semantic analysis for interactive multimedia services

Yiannis Kompatsiaris, Yannis Avrithis, Noel E. O'Connor
2008 Signal processing. Image communication  
This editorial introduces the Special Issue, which contains a selection of papers that present recent advances in a number of areas relating to semantic analysis for interactive multimedia services.  ...  Technologies for retrieving semantic information from multimedia content potentially enable new applications and services for both commercial and personal end users.  ...  Much work on semantic knowledge extraction in video is based on the assumption that a camera shot, rather than a video frame, is the atomic unit of access to the content.  ... 
doi:10.1016/j.image.2008.05.001 fatcat:wdhtwoopyjfvvpmp675e3wz4vu

A Survey on Visual Content-Based Video Indexing and Retrieval

Weiming Hu, Nianhua Xie, Li Li, Xianglin Zeng, S. Maybank
2011 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
This paper offers a tutorial and an overview of the landscape of general strategies in visual content-based video indexing and retrieval, focusing on methods for video structure analysis, including shot  ...  boundary detection, key frame extraction and scene segmentation, extraction of features including static key frame features, object features and motion features, video data mining, video annotation, video  ...  Thus, motion-based features for video retrieval can be divided into two categories: camera-based and object-based.  ... 
doi:10.1109/tsmcc.2011.2109710 fatcat:qtenus4htffcfbyuiwidgjojku

Survey of compressed-domain features used in audio-visual indexing and analysis

Hualu Wang, Ajay Divakaran, Anthony Vetro, Shih-Fu Chang, Huifang Sun
2003 Journal of Visual Communication and Image Representation  
Compressed-domain approaches avoid expensive computation and memory requirements involved in decoding and/or re-encoding.  ...  The paper is motivated by the myriad of active research works in extraction and application of compressed-domain features in various fields, such as indexing, filtering, and manipulation.  ...  from background/camera motion, and cluster video shots based on motion and color information in sports videos.  ... 
doi:10.1016/s1047-3203(03)00019-1 fatcat:5pueo6wembhafibi3wzqbuk2vi

Character index

2011 2011 IEEE International Conference on Multimedia and Expo  
doi:10.1109/icme.2011.6011827 fatcat:wjy7yvkmvbbf3hj4wbyjapx5gu

Video Content Modeling [chapter]

Tong Zhang, C.-C. Jay Kuo
2001 Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing  
This paper provides an overview of different video content modeling techniques employed in existing content-based video indexing and retrieval (CBVIR) systems.  ...  Finally, a hypothetical CBVIR system is outlined in the concluding remarks, which exploits object-based representation of MPEG-4 compressed bitstream and uses multimodal features based on high-level description  ...  [32] present a scene change detection method for compressed domain videos using stochastic sequential analysis theory.  ... 
doi:10.1007/978-1-4757-3339-6_2 fatcat:2cyk63bmcrgftd2hffsqsqhvai

Video retrieval and summarization

Nicu Sebe, Michael S. Lew, Arnold W.M. Smeulders
2003 Computer Vision and Image Understanding  
Furthermore, higher level representations which reflect the structure of the constituent video shots or semantic temporal information such as gestures could also aid in retrieving the right video scene  ...  In particular, we need robust techniques to index/retrieve and compress visual information, new scalable browsing algorithms allowing access to  ...  [10] propose a novel scheme for object-based video analysis and interpretation of human motion in sports video sequences based on automatic video object extraction, video object abstraction, and semantic  ... 
doi:10.1016/j.cviu.2003.08.003 fatcat:6azywnsaurerfbtvftnscl6jbm

Multimedia Content Analysis and Indexing for Filtering and Retrieval Applications

N. Dimitrova
1999 Informing Science  
This paper surveys techniques for content-based analysis, retrieval and filtering of digital images, audio and video and focuses on basic methods for extracting features that will enable indexing and search  ...  ic ca at ti io on ns s Abstract Today's multimedia landscape depends on advances in data compression technology coupled with high-bandwidth networks and storage capacity.  ...  Meng et al. propose object indexing, camera motion, prominent moving objects and shape extraction and processing to retrieve semantic context of video [43] .  ... 
doi:10.28945/605 fatcat:mdjq3nw7ajaajepqfrdy4jtvpa

Towards Ontological Cognitive System [chapter]

Carles Fernandez, Jordi Gonzàlez, João Manuel R. S. Tavares, F. Xavier Roca
2013 Lecture Notes in Computational Vision and Biomechanics  
The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance  ...  community to guide its steps towards a better attainment of such capabilities.  ...  These capabilities derive a series of tasks that are usually requested in the domain of multimedia semantics, such as automatic video annotation to enable query-based video retrieval.  ... 
doi:10.1007/978-94-007-0726-9_5 fatcat:kugu32atk5ahpcuppraqhhrsxi

Near-lossless semantic video summarization and its applications to video analysis

Tao Mei, Lin-Xie Tang, Jinhui Tang, Xian-Sheng Hua
2013 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
least semantic loss based on the summary, through which high-level semantic video analysis can be performed effectively.  ...  Based on the parameters in equation (2), a qualitative threshold-based method can be used to sequentially identify each of the camera motion categories in the order as follows: zoom → rotation → pan →  ... 
doi:10.1145/2487268.2487269 fatcat:qnonyt6dyjh7pcn3httg5eegau
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