A key aspect of imageretrieval using color, is the creation of robust and efficient indices. In particular, the color histogram remains the most popular index, due primarily to its simplicity. However, the color hist...
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A key aspect of imageretrieval using color, is the creation of robust and efficient indices. In particular, the color histogram remains the most popular index, due primarily to its simplicity. However, the color histogram has a number of drawbacks. Specifically, histograms capture only global activity, they require quantization to reduce dimensionality, are highly dependent on the chosen color space, have no means to exclude a certain color from a query and can provide erroneous results due to gamma nonlinearity. In this paper we present a vector angular distance measure which is implemented as part of our database system. Our system does away with histogram techniques for color indexing and retrieval and instead implements color vector techniques. We use color segmentation to extract regions of prominent color and use representative vectors from these extracted regions in the image indices. This way we end up with a much smaller index which does not have the granularity of a histogram. Instead similarity is based on our vector angular distance measure between a query color vector and the indexed representative vectors.
In this paper we propose a novel system of semantic feature extraction and retrieval for interior design and decoration application. The system, V2ID (Virtual Interior Design), uses colored texture and spatial edge la...
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In this paper we propose a novel system of semantic feature extraction and retrieval for interior design and decoration application. The system, V2ID (Virtual Interior Design), uses colored texture and spatial edge layout to obtain simple information about global room environment. We address the domain specific segmentation problem in our application and present techniques for obtaining semantic features from a room environment. We also discuss heuristics for making use of these features (color, texture, edge layout and shape) to retrieve objects from an existing database. The final resynthesized room environment with original scene and objects from database is created for the purpose of animation and virtual walk-through.
The Fractal Transform (FT) was originally introduced as a methodology for compressing digital images and representing them at different scales. The process of calculating an FT generates a great deal of information ab...
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The Fractal Transform (FT) was originally introduced as a methodology for compressing digital images and representing them at different scales. The process of calculating an FT generates a great deal of information about the affine similarities and dissimilarities of an image, most of which is discarded in compression applications. In this paper we introduce the concept of Fractal Transform Analysis and use it to derive new image descriptors. We present results of experiments in which description schemes comprised of some of these FT-based descriptors are applied to the problems of finding objects in an image similar to a given object, of indexing images, and of querying an image database consisting of about 17,000 images. Complexity and timing data are also presented.
In this paper, we propose a new image feature extraction method for MPEG compressed video. To minimize the MPEG decoding process, we use only DC values for Y, Cr, and Cb components for each macroblock. Then, we can ob...
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In this paper, we propose a new image feature extraction method for MPEG compressed video. To minimize the MPEG decoding process, we use only DC values for Y, Cr, and Cb components for each macroblock. Then, we can obtain a feature vector using the decoded DC values of Y, Cr, and Cb components for all macroblocks in an I frame. The feature vector consists of histograms for various colors, luminance, and edge types. In obtaining histograms for colors and luminance features, we consider the ratio of contributing pure colors and luminance to the chroma DC values for each macroblock. Then, we update all contributing colors and/or luminance histograms accordingly. Otherwise, if the macro block is classified as an edge block, then we update the corresponding edge type histogram. To demonstrate the performance of the proposed feature extraction method, we apply it to a scene change detection problem.
We have developed a wide-area-distributed storage system for multimedia databases that minimizes the possibility of simultaneous failure of multiple disks in the event of a major disaster. It features a RAID system wh...
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We have developed a wide-area-distributed storage system for multimedia databases that minimizes the possibility of simultaneous failure of multiple disks in the event of a major disaster. It features a RAID system whose member disks are spatially distributed over a wide area. Each node has a device that includes the controller of the RAID and the controller of the member disks controlled by other nodes. The devices in the node are connected to a computer using fiber optic cables and communicate using Fibre-Channel technology. Any computer at a node can utilize multiple devices connected by optical fibers as a single 'virtual disk'. The advantage of this system structure is that devices and fiber optic cables are shared by the computers. In this report, we first describe our proposed system and a prototype we used for testing. Then we discuss its performance, i.e., how the read and write throughputs are affected by data-access delay, the RAID level, and queuing.
image search has been actively studied in recent years. On the other hands, image browsing has received little attention. image browsing refers to the process of presenting some forms of overview or summary of the ima...
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image search has been actively studied in recent years. On the other hands, image browsing has received little attention. image browsing refers to the process of presenting some forms of overview or summary of the image relationships, thus facilitating a user to navigate across the data set and find images of interests. In this paper, we present a new data structure built on the multi-linearization of image attributes for efficient organization of the data set and fast visual browsing of the images. We describe new techniques for multi-linearization based on multiple space-filling curves and hierarchical clustering techniques. In addition to providing fast navigation, our proposed data structure allows computationally efficient insertion and deletion of images from the data set. We then present a novel image navigator and browser built on dual-linearization data structure and intuitive presentation of image relevance and relationships, demonstrate the image navigation process, and report results on 1000 and 22,000 imagedatabases. We also discuss how our data structure can be extended to support fast image search.
Multimedia data is generally stored in compressed form in order to efficiently utilize the available storage facilities. Access to archives is dependent on our ability to browse compressed multimedia information - ret...
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Multimedia data is generally stored in compressed form in order to efficiently utilize the available storage facilities. Access to archives is dependent on our ability to browse compressed multimedia information - retrieval and tracking from coded videodatabases. In this paper, a novel visual search engine for videoretrieval and tracking from compressed multimedia databases is proposed. The goal of the project is the implementation of a visual browser that operates in a distributed environment where users initiate video searches and retrieve relevant video information simultaneously from multiple video archives. Being presented with a query in the form of template images of objects, the system operates on the compressed video to find the images or video sequences where those objects are present and their positions in the image. Upon user's request, the system will decompress and display only the video sequences of interest.
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.
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.
This paper addresses the problem of recovering the semantic structure of broadcast news. A hierarchy of retrievable units is automatically constructed by integrating information from different media. The hierarchy pro...
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This paper addresses the problem of recovering the semantic structure of broadcast news. A hierarchy of retrievable units is automatically constructed by integrating information from different media. The hierarchy provides a compact yet meaningful abstraction of the broadcast news data similar to a conventional table of content that can serve as an effective index table, facilitating the capability of browsing through large amounts of data in a non-linear fashion. The recovery of the semantic structure of the data further enables the automated solutions in constructing visual representations that are relevant to the semantics as well as in establishing useful relationships among data units such as topic categorization and content based multimedia hyperlinking. Preliminary experiments of integrating different media for hierarchical segmentation of semantics have yielded encouraging results. Some of the results are presented and discussed in this paper.
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