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.
In this paper videos are analyzed to get a content-based decription of the video. The structure of a given video is useful to index long videos efficiently and automatically. A comparison between shots gives an overvi...
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ISBN:
(纸本)0819427527
In this paper videos are analyzed to get a content-based decription of the video. The structure of a given video is useful to index long videos efficiently and automatically. A comparison between shots gives an overview about cut frequency, cut pattern, and scene bounds. After a shot detection the shots are grouped into clusters based on their visual similarity. A time-constraint clustering procedure is used to compare only those shots that are positioned inside a time range. Shots from different areas of the video (e.g., begin/end) are not compared. With this cluster information that contains a list about shots and their clusters it is possible to calculate scene bounds. A labeling of all clusters gives a declaration about the cut pattern. It is easy now to distinguish a dialogue from an action scene. The final content analysis is done by the imageMiner* system. The imageMiner system developed at the University of Bremen of the image Processing Department of the Center for Computing Technology realizes content-based imageretrieval for stillimages through a novel combination of methods and techniques of computer vision and artifical intelligence. The imageMiner system consists of three analysis modules for computer vision, namely for color, texture, and contour analysis. Additionally exists a module for object recognition. The output of the object recognition module can be indexed by a text retrieval system. Thus, concepts like forestscene may;be searched for. We combine the stillimage analysis with the results of the video analysis in order to retrieve shots or scenes.
This paper introduces a model of spatio-temporal database that we are developing to query interesting events in video sequences. The database that we are designing is pushing the state of the art for a number of field...
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ISBN:
(纸本)0819431273
This paper introduces a model of spatio-temporal database that we are developing to query interesting events in video sequences. The database that we are designing is pushing the state of the art for a number of fields, and there are many issues that are still waiting a satisfactory solution. In this paper we present our (albeit still partial) answer to some of these problems, and the future directions of our work. Our design is divided in two layers: a Logbook which operates as a short time repository of unsummarized and unprocessed data, and a long term spatio-temporal database which stores and queries sumamrized data.
video data management is fast becoming one of the most important topics in multimedia databases. Most of the recent work on videodatabases has so far focused on video classification, feature extraction, spatial reaso...
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ISBN:
(纸本)0819420441
video data management is fast becoming one of the most important topics in multimedia databases. Most of the recent work on videodatabases has so far focused on video classification, feature extraction, spatial reasoning and imageretrieval (video access);little work has been done on supporting advanced video editing and production activities, nor has there been much work done on providing facilities for efficient and versatile video data management. In this paper, we describe the development of an experimental video database system being implemented at HKUST, which employs extended object-oriented features and techniques. By incorporating conceptual object clustering concepts and techniques, it enables users to dynamically form, among other things, video programs (or segments) from existing objects based on semantic features/index terms. A prototype of this system has been constructed, using a persistent object storage manager (viz. EOS), on Sun4 workstations.
Illumination invariance is of paramount importance to annotate video sequences stored in large videodatabases consistently. Yet, popular texture analysis methods such as multichannel filtering techniques do not yield ...
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Illumination invariance is of paramount importance to annotate video sequences stored in large videodatabases consistently. Yet, popular texture analysis methods such as multichannel filtering techniques do not yield illumination-invariant texture representations. In this paper, we assess the effectiveness of three illumination normalisation schemes for texture representations derived from Gabor filter outputs. The schemes aim at overcoming intensity scaling effects due to changes in ilumination conditions. A theoretical analysis and experimental results enable us to select one scheme as the most promising one. In this scheme, a normalising factor is derived at each pixel by combining the energy responses of different filters at that pixel. The scheme overcomes illumination variations well, while still preserving discriminatory textural information. Further statistical analysis may shed light on other interesting properties or limitations of the scheme.
Content based retrieval on large multimedia database attracts the interests of many researchers, but the database architecture needed for content based retrieval is still an open problem. Traditional relation database...
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ISBN:
(纸本)0819431273
Content based retrieval on large multimedia database attracts the interests of many researchers, but the database architecture needed for content based retrieval is still an open problem. Traditional relation database system does not support the high-dimension feature form content description and indexing, thus is limited in its content based retrieval function. Some systems do support high-dimension feature form content description and indexing, but lacks descriptions and query expressions on media object content and relations. In this paper, we present our study results on query mechanism and proposed CbEEpr - a power flexible query expression mechanism on media object. Based on CbExpr we proposed GMA (general mediabase architecture) -a general architecture for management and content based retrieval on large media databases, and videoBase - a content based videoretrieval system is present as example of GMA. Basic thoughts, considerations, and definitions are presented in the paper, also with some implementation details.
The virtual digital library, a concept that is quickly becoming a reality, offers rapid and geography-independent access to stores of text, images, graphics, motion video and other datatypes. Furthermore, a user may m...
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ISBN:
(纸本)0819420441
The virtual digital library, a concept that is quickly becoming a reality, offers rapid and geography-independent access to stores of text, images, graphics, motion video and other datatypes. Furthermore, a user may move from one information source to another through hypertext linkages. The projects described here further the notion of such an information paradigm from an end user viewpoint.
Various methods of automatic shot boundary detection have been proposed and claimed to perform reliably. Although the detection of edits is fundamental to any kind of video analysis since it segments a video into its ...
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Various methods of automatic shot boundary detection have been proposed and claimed to perform reliably. Although the detection of edits is fundamental to any kind of video analysis since it segments a video into its basic components, the shots, only few comparative investigations on early shot boundary detection algorithms have been published. These investigations mainly concentrate on measuring the edit detection performance, however, do not consider the algorithms' ability to classify the types and to locate the boundaries of the edits correctly. This paper extends these comparative investigations. More recent algorithms designed explicitly to detect specific complex editing operations such as fades and dissolves are taken into account, and their ability to classify the types and locate the boundaries of such edits are examined. The algorithms' performance is measured in terms of hit rate, number of false hits, and miss rate for hard cuts, fades, and dissolves over a large and diverse set of video sequences. The experiments show that while hard cuts and fades can be detected reliably, dissolves are still an open research issue. The false hit rate for dissolves is usually unacceptably high, ranging from 50% up to over 400%. Moreover, all algorithms seem to fail under roughly the same conditions.
Modern computer applications use enormous volumes of rich data like video, stillimages, and text, as well as more conventional numeric and character data. Managing huge volumes of such diverse data requires a databas...
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ISBN:
(纸本)081941767X
Modern computer applications use enormous volumes of rich data like video, stillimages, and text, as well as more conventional numeric and character data. Managing huge volumes of such diverse data requires a database. Content queries, such as 'find me the color images with red components higher than this threshold,' require that the database system be able to apply the qualification directly. Relational database systems that store images as untyped binary large objects (BLOBS) cannot apply qualifications like this, because the database system does not understand the contents of the BLOB. Object-Relational Database Management Systems (ORDBMS), on the other hand, allow users to extend the set of types and functions known to the database system. Programmers can write code that is dynamically loaded into the database server, and that operates on complex data types such as images. Those functions can be used in standard SQL queries, and the database manager can use new types and function results in indices to support fast queries on complex data. In addition, the query optimizer can be told how expensive the new functions are, so that it chooses an optimal strategy for satisfying complicated queries with many different predicates in their qualifications.
In this paper we address the problem of choosing appropriate features to describe the content of still pictures or video sequences including audio. As the computational analysis of these features is often time-consumi...
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ISBN:
(纸本)0819431273
In this paper we address the problem of choosing appropriate features to describe the content of still pictures or video sequences including audio. As the computational analysis of these features is often time-consuming it is useful to identify a minimal set allowing for an automatic classification of some class or genre. Further it can be shown that deleting the coherence of the features characterizing some class is not suitable to guarantee an optimal classification result. The central question of the paper is thus which features should be selected and how they should be weighted to optimize a classification problem.
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