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conference on storage and retrieval for Media databases 2001

作者： Ekin, A Tekalp, AM Mehrotra, R Univ Rochester Dept Elect & Comp Engn Rochester NY 14627 USA

ISBN: (纸本)0819439932

We present a generic model to describe image and video content by a combination of semantic entities and low level features for semantically meaningful and fast retrieval. The proposed model includes semantic entities such as Object, Event and Actors to express relations between title first two. The use of Actors entity increases the efficiency of certain types of search, while the use of semantic and linguistic roles increases the expression capability of the model. The model also contains links to high-level media segments such as actions and interactions, and low level media segments such as elementary motion and reaction units, as well as low-level features such as motion parameters and trajectories. Based on this model, we propose image and video retrieval combining semantic and low-level information. The retrieval performance of our system is tested by using query-by-annotation, query-by-example, query-by-sketch, and a combination of them.

关键词： semantic model video events and objects object motion description elementary motion units elementary reaction units trajectory matching semantic retrieval

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video classification using speaker identification 5

Video classification using speaker identification

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conference on storage and retrieval for image and video databases V

作者： Patel, NV Sethi, IK Wayne State Univ. (United States)

ISBN: (纸本)0819424331

video content characterization is a challenging problem in video databases. The aim of such characterization is to generate indices that can describe a video clip in terms of objects and their actions in the clip. Generally, such indices are extracted by performing image analysis on video clips. Many such indices can also be generated by analyzing the embedded audio information of video clips. Indices pertaining to context, scene emotion, and actors or characters present in a video dip appear especially suitable for generation via audio analysis techniques of keyword spotting, and speech and speaker recognition. In this paper, we examine the potential of speaker identification techniques for characterizing video clips in terms of actors present in them. We describe a three-stage processing system consisting of a shot boundary detection stage, an audio classification stage, and a speaker identification stage to determine the presence of different actors in isolated shots. Experimental results using the movie Few Good Men are presented to show the efficacy of speaker identification for labeling video clips in terms of persons present in them.

关键词： video indexing speaker identification nearest neighbor classification cepstral coefficients audio classification

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Discovering video structure using the pseudo-semantic trace

Discovering video structure using the pseudo-semantic trace

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conference on storage and retrieval for Media databases 2001

作者： Taskiran, CM Bouman, CA Delp, EJ Purdue Univ Video & Image Proc Lab Sch Elect & Comp Engn VIPER W Lafayette IN 47907 USA

ISBN: (纸本)0819439932

In this paper we describe a framework of analyzing programs belonging to different TV program genres using Hidden Markov Models and pseudo-semantic features derived from video shots. Clustering using Gaussian mixture models is used to determine the order of the models. Results for initial genre classification experiments using two simple features derived from video shots are given.

关键词： video database hidden markov model pseudo-semantic feature

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image SEARCHING IN A SHIPPING PRODUCT

IMAGE SEARCHING IN A SHIPPING PRODUCT

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conference on storage and retrieval for image and video databases iiI

作者： EQUITZ, W STORM SOFTWARE MT VIEWCA 94043

ISBN: (纸本)081941767X

Searching in image databases using image content has made the transition from the laboratory to consumer software. Storm Software is a pioneer in bringing these techniques to shrink-wrapped software applications, and this presentation describes some of the methods we use in our products and some of the experiences we have had in bringing this new technology to consumers. We describe the scope of the problem we are trying to solve as well as some of the algorithms and interfaces we used. We also describe some of the rationales (based on theory as well as on user testing) we had for the various design decisions we made. Finally, we describe some of the challenges and opportunities we see ahead. Descriptions and screen shots of two software products implementing image searching (EasyPhoto and Apple PhotoFlash) are provided. Both products were developed by Storm Software.

关键词： image SEARCH QUERY BY image CONTENT image DATABASE QBIC COMMERCIAL SOFTWARE

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Content-based analysis and indexing of sports video

Content-based analysis and indexing of sports video

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storage and retrieval for Media databases 2002 conference

作者： Luo, M Bai, XS Xu, GY Tsinghua Univ Dept Comp Sci & Technol State Key Lab Intelligent Technol & Syst Beijing 100084 Peoples R China

ISBN: (纸本)0819444162

An explosion of on-line image and video data in digital form is already well underway. With the exponential rise in interactive information exploration and dissemination through the World-Wide Web, the major inhibitors of rapid access to on-line video data are the management of capture and storage, and content-based intelligent search and indexing techniques. This paper proposes an approach for content-based analysis and event-based indexing of sports video. It includes a novel method to organize shots-classifying shots as close shots and far shots, an original idea of blur extent-based event detection, and an innovative local mutation-based algorithm for caption detection and retrieval. Results on extensive real TV programs demonstrate the applicability of our approach.

关键词： video indexing caption detection and retrieval shot segmentation shot classification blur extent event detection

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video searching and retrieval using scene classification in multimedia databases 2

Video searching and retrieval using scene classification in ...

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2nd International conference for Emerging Technology, INCET 2021

作者： Haloi, Pranabjyoti Bhuyan, M.K. Indian Institute of Technology Guwahati Department of Electronics and Electrical Engineering Guwahati India

ISBN: (纸本)9781728170299

image and video indexing techniques play a key role in content-based searching in multimedia databases. A novel efficient video similarity search approach for content-based video retrieval in a large storage device is proposed. A compressed domain feature is used to classify the scenes of a video sequence. The performance of the said feature in classifying the scenes is evaluated by considering different feature lengths. Subsequently, a novel searching algorithm is proposed based on entropy of the image. This method incorporates temporal information of the video during video retrieval. Additionally, the proposed system has the facility to query both by video and by image. The 92.3% accuracy of the proposed method exceeded that of the VA-file 81.0% and OVA-file 76.4% methods and the computational complexity was lower than the VA-file method. This demonstrates the efficiency and effectiveness of the proposed method. © 2021 IEEE.

关键词： Classification (of information)

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Fast edge map extraction from MPEG compressed video data for video parsing

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 710-721页

作者： Song, Byung Cheol Ra, Jong Beom Korea Advanced Inst of Science and Technology Taejon Korea Republic of

For the last few years, shot boundary detection has been recognized as an important research issue on video retrieval. Also as a preliminary step for the task, it is essential to extract salient features from videos. Recently, it has become common to perform the two tasks in compressed domain to alleviate their computational costs. In this paper, we propose novel shot boundary detection technique, which uses two feature images, or DC and edge images, extracted directly from MPEG compressed video. While a DC image can be easily obtained, edge image extraction usually requires considerable computational burden. For fast edge image extraction, we suggest to utilize only a few AC coefficients of each DCT block in motion compensated P-frames and B-frames as well as I-frames. This drastically reduces the computational burden compared to edge extraction in the spatial domain. In order to further reduce the computational burden, another edge image extraction technique is also suggested on the basis of AC prediction using DC images. By using the edge energy diagram obtained from edge images and histograms from DC images, shot boundaries such as abrupt transitions, fades, and dissolves are detected automatically. Simulation results show that the proposed techniques are fast and effective.

关键词： Feature extraction

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imageGREP: Fast visual pattern matching in image databases 5

ImageGREP: Fast visual pattern matching in image databases

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conference on storage and retrieval for image and video databases V

作者： White, DA Jain, R Univ. of California/San Diego (United States)

ISBN: (纸本)0819424331

Most current image retrieval systems use holistic comparisons that require a global match between images or presegmented object in images. However, often the user of an image database system is interested in a local match between images. For example, ''Find images from the database with something like this anywhere in the image'' or ''Find images with something like this in some region of any image in the database'' or ''Find images with this spatial configuration of regions like this.'' In this paper, we provide an overview of a new framework that should help to allow these types of queries to be answered efficiently. In order to illustrate the usefulness of our framework, we have developed a complete image retrieval system based on local color information. Our system features fully automatic insertion and very efficient query execution, rivaling the efficiency of systems that can only handle global image comparisons. The query execution engine, called the imageGREP Engine, can process queries at a speed of approximately 3000 images per second (or better) on a standard workstation when the index can be stored in main memory. In the future, we believe our framework should be used in other domains and applications, to handle queries based on texture or other material properties and perhaps domain specific image properties.

关键词： content-based image databases image retrieval local image matching visual pattern matching image classifiers

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Multimedia information retrieval by analysing content and learning from examples

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 63-74页

作者： Ganapathy, S.Kicha Lei, Zhibin Safranek, Robert J. Bell Lab Murray Hill United States

Multimedia Information Systems are experiencing a tremendous growth as a direct consequence of the popularity and pervasive use of world wide web. As a consequence, it is becoming increasingly important to provide efficient and flexible solutions for accessing and retrieving multimedia data. images and video are emerging as significant data types in multimedia systems. And yet, most commercial systems are still text and key-word based and do not fully exploit the image content of these systems. We believe that there is an opportunity to build a novel interactive multimedia system for some specific applications in electronic commerce. In this paper we present an overview of our approach, the rationale behind it and the problems that are inherent in building such a system. We address some of the technical issues in representing and analysing image primitive features. These are the building blocks of any such systems. They can be generalized into a much broader range of applications as well.

关键词： Multimedia systems

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Model-based semantic object extraction for content-based video representation and indexing

Model-based semantic object extraction for content-based vid...

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conference on storage and retrieval for Media databases 2001

作者： Fan, J Yau, DKY Hacid, MS Elmagarmid, AK Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

ISBN: (纸本)0819439932

This paper proposes an integrated system for supporting content-based video retrieval and browsing over networks. An automatic semantic video object extraction technique for providing more compact video representation is developed. The video images are first partitioned into a set of homogeneous regions with accurate boundaries by integrating the results of color edge detection and region growing procedures. The object seeds, which are the intuitive and representative part of the semantic objects, are detected from these obtained homogeneous image regions. The semantic objects are then generated by a seeded region aggregation or a human interaction procedure. These obtained semantic objects are tracked along the time axis for exploiting their temporal correspondences among frames. Given the semantic video objects represented by a set of visual features, a seeded semantic video content clustering technique is developed for providing more effective video indexing, retrieval and browsing.

关键词： object extraction tracking video representation clustering indexing retrieval and browsing

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