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.
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.
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.
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.
databases are increasingly being used to store multimedia objects such as maps, images, audio, and video. storage and retrieval of these objects is accomplished using multidimensional index structures such as R*-trees...
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databases are increasingly being used to store multimedia objects such as maps, images, audio, and video. storage and retrieval of these objects is accomplished using multidimensional index structures such as R*-trees and SS-trees. As dimensionality increases, query performance in these index structures degrades. This phenomenon, generally referred to as the dimensionality curse, can be circumvented by reducing the dimensionality of the data. Such a reduction is, however, accompanied by a loss of precision of query results. Current techniques such as QBIC use SVD transform-based dimensionality reduction to ensure high query precision. The drawback of this approach is that SVD is expensive to compute and, therefore, not readily applicable to dynamic databases. In this paper, we propose novel techniques for performing SVD-based dimensionality reduction in dynamic databases. When the data distribution changes considerably so as to degrade query precision, we recompute the SVD transform and incorporate it in the existing index structure. For recomputing the SVD-transform, we propose a novel technique that uses aggregate data from the existing index rather than the entire data. This technique reduces the SVD-computation time without compromising query precision. We then explore efficient ways to incorporate the recomputed SVD-transform in the existing index structure. These techniques reduce the computation time by a factor of 20 in experiments on color and texture image vectors. The error due to approximate computation of SVD is less than 10%. (C) 1999 Academic Press.
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 presents a simple and effective pre-processing method developed for the segmentation of MPEG compressed video sequences. The proposed method for scene-cut detection only involves computing the number of bit...
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This paper presents a simple and effective pre-processing method developed for the segmentation of MPEG compressed video sequences. The proposed method for scene-cut detection only involves computing the number of bits spent for each frame (encoding cost data), thus avoiding decoding the bitstream. The information is separated into I-, P-, B-frames, thus forming 3 vectors which are independently processed by a new peak detection algorithm based on overcomplete filter banks and on joint thresholding using a confidence number. Each processed vector yields a set of candidate frame numbers, i.e. 'hints' of positions where scene-cuts may have occurred. The 'hints' for all frame types are recombined into one frame sequence and clustered into scene cuts. The algorithm was not designed to distintuish among types of cuts but rather to indicate its position and duration. Experimental results show that the proposed algorithm is effective in detecting abrupt scene changes as well as gradual transitions. For precision demanding applications, the algorithm can be used with a low confidence factor just to select the frames that are worth being investigated by a more complex algorithm. The algorithm is not particularly tailored to MPEG and can be applied to most video compression techniques.
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