image histogram is an image feature widely used in content-based imageretrieval and video segmentation. It is simple to compute yet very effective as a feature in detecting image-to-image similarity, or frame-to-fram...
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ISBN:
(纸本)0819431273
image histogram is an image feature widely used in content-based imageretrieval and video segmentation. It is simple to compute yet very effective as a feature in detecting image-to-image similarity, or frame-to-frame dissimilarity. While the image histogram captures the global distribution of different intensities or colors well, it does not contain any information about the spatial distribution of pixels. In this paper, we propose to incorporate spatial information into the image histogram by computing features from the spatial distance between pixels belonging to the same intensity or color. In addition to the frequency count of the intensity or color, the mean, variance, and entropy of the distances are computed to form an Augmented image Histogram. Using the new feature, we preformed experiments on a set of color images and a color video sequence. Experimental results demonstrate that the Augmented image Histogram performs significantly better than the conventional color histogram, both in imageretrieval and video shot segmentation.
video content characterization is a challenging problem in videodatabases. 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. Gen...
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ISBN:
(纸本)0819424331
video content characterization is a challenging problem in videodatabases. 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.
In order to flexibly and efficiently store, manage, and present video data streams, continuous video data must be chopped into video objects and stored into database. This paper investigates systematic strategies for ...
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ISBN:
(纸本)0819420441
In order to flexibly and efficiently store, manage, and present video data streams, continuous video data must be chopped into video objects and stored into database. This paper investigates systematic strategies for supporting continuous and synchronized presentation of video data streams in multimedia database systems. Compressed video data streams are segmented and stored as sets of video objects coupled with specified synchronization requirements. Strategies for efficiently scheduling and buffering video objects are presented which guarantee the hiccup-free presentations of video streams. Delay effects are considered in these strategies. We propose to extend the existing object-oriented database system (OODBS) techniques to include the proposed video presentation mechanisms. We are currently designing and implementing a multimedia presentation tool (termed MediaShow) on top of O2, a well-known OODBS, as a basis for our implementation. However, the design strategies can be generally used in any OODBS environments that support C++ interface.
Real-world video-based applications require database technology that is capable of storing digital video in the form of videodatabases and providing content-based video search and retrieval. Methods for handling trad...
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Real-world video-based applications require database technology that is capable of storing digital video in the form of videodatabases and providing content-based video search and retrieval. Methods for handling traditional data storage, query, search, retrieval, and presentation cannot be extended to provide this functionality. The VDBMS research initiative is motivated by the requirements of video-based applications to search and retrieve portions of video data based on content and by the need for testbed facilities to facilitate research in the area of video database management. In this paper we describe the VDBMS video database research platform, a system that supports comprehensive and efficient database management for digital video. Our fundamental concept is to provide a full range of functionality for video as a well-defined abstract database data type, with its own description, parameters, and applicable methods. Research problems that are addressed by VDBMS to support the handling of video data include MPEG7 standard multimedia content representation, algorithms for image-based shot detection, image processing techniques for extracting low-level visual features, a high-dimensional indexing technique to access the high-dimensional feature vectors extracted by image preprocessing, multimedia query processing and optimization, new query operators, real-time stream management, a search-based buffer management policy, and an access control model for selective, content-based access to streaming video. VDBMS also provides an environment for testing the correctness and scope of new video processing techniques, measuring the performance of algorithms in a standardized way, and comparing the performance of different implementations of an algorithm or component. We are currently developing video component wrappers with well-defined interfaces to facilitate the modification or replacement of video processing components. The ultimate goal of the VDBMS project is a fle
imageretrieval systems that compare the query image exhaustively with each individual image in the database are not scalable to large databases. A scalable search system should ensure that the search time does not in...
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ISBN:
(纸本)0819431273
imageretrieval systems that compare the query image exhaustively with each individual image in the database are not scalable to large databases. A scalable search system should ensure that the search time does not increase linearly with the number of images in the database. We present a clustering based indexing technique, where the images in the database are grouped into clusters of images with similar color content using a hierarchical clustering algorithm. At search time the query image is not compared with all the images in the database, but only with a small subset. Experiments show that this clustering based approach offers a superior response time with a high retrieval accuracy. Experiments with different database sizes indicate that for a given retrieval accuracy the search time does not increase linearly with the database size.
This paper presents algorithms to deal with problems associated with indexing high-dimensional feature vectors that characterize video data. Indexing high dimensional vectors is well known to be computationally expens...
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This paper presents algorithms to deal with problems associated with indexing high-dimensional feature vectors that characterize video data. Indexing high dimensional vectors is well known to be computationally expensive. Our solution is to optimally split the high dimensional vector into a few low dimensional feature vectors and querying the system for each feature vector. This involves solving an important sub-problem: developing a model of retrieval that enables us to query the system efficiently. Once we formulate the retrieval problem in terms of a retrieval model, we present an optimality criterion to maximize the number of results using this model. The criterion is based on a novel idea of using the underlying probability distribution of the feature vectors. A branch-and-prune strategy optimized per each query, is developed. This uses the set of features derived from the optimality criterion. Our results show that the algorithm performs well, giving a speedup of a factor of 25 with respect to a linear search while retaining the same level of Recall.
Most current imageretrieval 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 m...
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ISBN:
(纸本)0819424331
Most current imageretrieval 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 imageretrieval 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.
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 ...
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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.
An experimental video server for middle-scale video-on-demand services that uses a 'redundant double-layered disk array' can read out 100 MPEG-1 1.5-Mbps video streams simultaneously with a response time of un...
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ISBN:
(纸本)0819420441
An experimental video server for middle-scale video-on-demand services that uses a 'redundant double-layered disk array' can read out 100 MPEG-1 1.5-Mbps video streams simultaneously with a response time of under one second through an FDDI-LAN. An exclusive data method that switches between normal data and fast data and a skip-search method are used to provide fast visual search. The gateway connecting the video server LAN to a 6.312-Mbps constant bit-rate line allows broadcast services to be integrated with on- demand services. The protocol implemented in this gateway controls the visual search rate, corrects errors in downloaded data, and accelerates the playback mode changes.
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 eff...
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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.
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