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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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 CbExpr - a powerful 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.
Organizing video shots into hierarchy structures is very important for efficient browsing and retrieval on large videodatabases, and many shot organizing methods have been proposed. Most algorithms are based on autom...
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Organizing video shots into hierarchy structures is very important for efficient browsing and retrieval on large videodatabases, and many shot organizing methods have been proposed. Most algorithms are based on automatic clustering schemes, which usually fail to give satisfactory results in real applications. In this paper, we proposed a preprocessing technology for interactive shot organizing - similarity sequence. It differs from traditional shot organizing methods in that it does not classify shots, instead it only reorders the shot sequence so that similar shots appear near each other, thus provides an effective interactive shot organizing interface and leaves the classification work to the user. A measure called similarity length was introduced to evaluate the similarity between adjacent shots in shot sequence, and an improved genetic algorithm was developed to calculate the similarity sequence. Basic thoughts and implementation details are provided, also with experiment results on real videos and analysis.
The color hologram of an image has been widely used as a feature descriptor for the image in content-based retrieval applications. In this paper, some results from our investigation efforts into to usage are reported....
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The color hologram of an image has been widely used as a feature descriptor for the image in content-based retrieval applications. In this paper, some results from our investigation efforts into to usage are reported. We outline three typical color space quantization schemes used in our experiments and introduce the soft-decision histogramming method to eliminate the discontinuity problem in traditional color histogram population process. Then, to improve the effectiveness of color histogram based retrieval algorithms, several similarity metrics are proposed for comparing color histograms, including three special forms of the Kantorovich metric.
We present a fast algorithm for computing the singular value decomposition (SVD) of a matrix consisting of the frames from a video sequence. The computational efficiency of this algorithm derives from the observation ...
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We present a fast algorithm for computing the singular value decomposition (SVD) of a matrix consisting of the frames from a video sequence. The computational efficiency of this algorithm derives from the observation that portions of a video sequence will consist of sets of correlated frames. We then show that the information obtained from the SVD can be used to analyze video sequences to obtain information such as scene breaks, scene query, reduced-order shot representation and key frame determination. We illustrate this approach on several video sequences.
The amount of digitized video in video archives is becoming so huge that easier access and content browsing tools are desperately needed. Also, video is no longer one big piece of data but a collection of useful small...
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The amount of digitized video in video archives is becoming so huge that easier access and content browsing tools are desperately needed. Also, video is no longer one big piece of data but a collection of useful smaller building blocks that can be accessed and used independently from the original context of presentation. In this paper, we demonstrate a content model for audio-video sequences with the purpose of enabling the automatic generation of video summaries. The model is based on descriptors which indicate various properties and relations of audio and video segments. In practice, these descriptors could either be generated automatically by analysis methods, or produced manually (or computer-assisted) by the content provider himself. We analyze the requirements and characteristics of the different data segments with respect to the problem of summarization, and we define our model as a set of constraints which allow to produce good quality summaries.
video Segmentation plays an integral role in many multimedia applications such as digital libraries, content management systems, and various other video browsing, indexing, and retrieval systems. Many algorithms for s...
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video Segmentation plays an integral role in many multimedia applications such as digital libraries, content management systems, and various other video browsing, indexing, and retrieval systems. Many algorithms for segmentation of video have appeared in the past few years. Most of these algorithms perform well on cuts, but yield poor performance on gradual transitions or special effect edits. A complete video segmentation system must achieve good performance on special effect edit detection also. In this paper, we discuss the performance of our videoTrails based algorithms with other existing special effect edit detection algorithms in literature. Results from experiments testing for the ability to detect edits from TV programs ranging from commercials to news magazine programs, and also diverse special effect edits introduced by us have been shown.
We have developed a TV-on-demand system that provides playback of a television program after a period ranging from a few seconds to one week after broadcast, and have conducted usage trials in cooperation with a telev...
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We have developed a TV-on-demand system that provides playback of a television program after a period ranging from a few seconds to one week after broadcast, and have conducted usage trials in cooperation with a television station in Nagano Prefecture of Japan. This system has been achieved through the development of various technologies such as automatic updating of stored television programs and contents retrieval by telop characters. Users in the trials can begin playback of a television program immediately after its broadcast has begun. The purpose of the trials was to evaluate the system's usability in applications such as contents retrieval, selective viewing of commercials, and customer service at the television station. This paper presents applied technologies and some experimental results and also addresses a new direction of information retrieval system based on the evaluation of the usage trials.
In this paper we introduce our approach to multimedia database interfaces. Although we deal mainly with imagedatabases, most of the ideas we present can be generalized to other types of data. We argue that, when deal...
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In this paper we introduce our approach to multimedia database interfaces. Although we deal mainly with imagedatabases, most of the ideas we present can be generalized to other types of data. We argue that, when dealing with complex data, such as images, the problem of access must be redefined along different lines than text databases. In multimedia databases, the semantics of the data is imprecise, and depends in part on user's interpretation. This observation made us consider the development of interfaces in which the user explores the database rather than querying it. In this paper we give a brief justification of our position and present the exploratory interface that we have developed for our image database El nino.
Content Based imageretrieval has recently become one of the most active research areas, due to the massive increase in the amount and complexity of digitized data being stored, transmitted and accessed. We present he...
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Content Based imageretrieval has recently become one of the most active research areas, due to the massive increase in the amount and complexity of digitized data being stored, transmitted and accessed. We present here a prototype implementation of DRAWSEARCH, an imageretrieval by content system that uses color and shape (and texture in the near future) features to index and retrieve images. The system, currently being tested and improved, is designed to increase interactivity with users posing queries over the Internet and avails of a Java client for query by sketch. It also implements relevance feedback to allow users dynamically refine queries. Experiments show that the proposed approach can greatly reduce the user's effort to compose a query while capturing his/her information need with greater precision.
While current approaches for video segmentation and indexing are mostly focused on visual information, audio signals may actually play a primary role in video content parsing. In this paper, we present an approach for...
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While current approaches for video segmentation and indexing are mostly focused on visual information, audio signals may actually play a primary role in video content parsing. In this paper, we present an approach for automatic segmentation, indexing, and retrieval of audiovisual data based on audio content analysis. The accompanying audio signal of audiovisual data is first segmented and classified into basic types, i.e. speech, music, environmental sound, and silence. This coarse-level segmentation and indexing step is based on morphological and statistical analysis of several short-term features of the audio signals. Then, environmental sounds are classified into finer classes such as applause, explosion, bird's sound, etc. This fine-level classification and indexing step is based on time-frequency analysis of audio signals and the use of hidden Markov model (HMM) as the classifier. On top of this archiving scheme, an audiovisual data retrieval system is proposed. Experimental results show that the proposed approach has an accuracy rate higher than 90% for the coarse-level classification, and higher than 85% for the fine-level classification. Examples of audiovisual data segmentation and retrieval are also provided.
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