Color is one of the most widely used features for image similarity retrieval. Most of the existing image similarity retrieval schemes employ either global or local color histogramming. In this paper, we explore the us...
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ISBN:
(纸本)0819427527
Color is one of the most widely used features for image similarity retrieval. Most of the existing image similarity retrieval schemes employ either global or local color histogramming. In this paper, we explore the use of localized dominant hue and saturation values for color-based image similarity retrieval. This scheme results in a relatively compact representation of color images for similarity retrieval. Experimental results comparing the proposed representation with global and local color histogramming are presented to show the efficacy of the suggested scheme.
In this paper me present a framework for content based query and retrieval of information from large videodatabases. This framework enables content based retrieval of video sequences by characterizing the sequences u...
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ISBN:
(纸本)0819424331
In this paper me present a framework for content based query and retrieval of information from large videodatabases. This framework enables content based retrieval of video sequences by characterizing the sequences using motion, texture and colorimetry cues. This characterization is biologically inspired and results in a compact parameter space where every segment of video is represented by an 8 dimensional vector. Searching and retrieval is done in real-time with accuracy in this parameter space. Using this characterization, we then evolve a set of discriminators using Genetic Programming. Experiments indicate that these discriminators are capable of analyzing and characterizing video. The videoBook is able to search and retrieve video sequences with 92% accuracy in real-time. Experiments thus demonstrate that the characterization is capable of extracting higher level structure from raw pixel values.
A prototype of the content-based imageretrieval system is implemented based on the algorithms introduced in this paper. The image contents at the high levels are extracted. The fuzzy C-means classifier is employed to...
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A prototype of the content-based imageretrieval system is implemented based on the algorithms introduced in this paper. The image contents at the high levels are extracted. The fuzzy C-means classifier is employed to compute the object clusters and provide useful information for overlapped clusters. The automatic image segmentation and categorisation is achieved. To obtain the context for imageretrieval, the subjective context and the objective context are modelled by means of the fuzzy sets theory. The system is able to trace the users' interactions during retrieval. The refinements of the retrieval results can be made while the users are submitting the queries telling the specific requirements.
With the abstraction of digital video as the corresponding binary video- a process which upon numerous subjective experimentation seems to preserve (most of the) intelligibility of video content- we can pursue a preci...
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With the abstraction of digital video as the corresponding binary video- a process which upon numerous subjective experimentation seems to preserve (most of the) intelligibility of video content- we can pursue a precise and analytic approach to (digital videostorage and retrieval) algorithm design that are based upon geometrical (morphological) intuition. The foremost and tangible general benefit of such abstraction, however, is the immediate reductions of both data and computational complexities involved in implementing various algorithms and databases. The general paradigm presented may be utilized to address all issues pertaining to video library construction including visualization, optimum feedback query generation, object recognition, e.t.c., but the primary focus of attention in this paper are the ones pertaining to detection of fast (including presence of flashlights) and gradual scene changes (such as dissolves, fades, and various special effects such as wipes). Upon simulation we observed that we can achieve performances comparable to those of others with drastic reductions in both storage and computational complexities. Furthermore, since the conversion from grayscale to binary videos can be performed directly (with minimal additional computation) in the compressed domain by thresholding on the DCT DC coefficients themselves (or by using the contour information attached to MPEG4 formats), the algorithms presented herein are ideally suited for performing fast (on-the-fly) determinations of scene change, object recognition and/or tracking, and other more intelligent tasks traditionally requiring heavy demand on computational and/or storage complexities. The fast determinations may then be used on their own merits or can be used in conjunction or complementation with other higher-layer information in the future.
The development of increasingly complex multimedia applications calls for new methodologies for the organization and retrieval of still images and video sequences. Query and retrieval methods based on image content pr...
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ISBN:
(纸本)0819424331
The development of increasingly complex multimedia applications calls for new methodologies for the organization and retrieval of still images and video sequences. Query and retrieval methods based on image content promise good results, are currently widely investigated and, to some extent, already commercially available. Yet a large number of issues remain unsolved. In this paper we describe some results of a study on similarity evaluation in imageretrieval using color, object orientation and relative position as content features. A simple prototype system is also introduced that computes the feature descriptors and performs queries. Although not trivial, the features extraction process is completely automated and requires no user intervention. The system is admittedly not a general purpose tool, but is oriented to thematic image repositories where the semantics of stored images are limited to a specific domain.
video parsing is an important step in content-based indexing techniques where the input video is decomposed into segments with uniform content. In video parsing detection of scene changes is one of the approaches wide...
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video parsing is an important step in content-based indexing techniques where the input video is decomposed into segments with uniform content. In video parsing detection of scene changes is one of the approaches widely used for extracting key frames from the video sequence. In this paper, an algorithm based on motion vectors is proposed to detect sudden scene changes and gradual scene changes (camera movements such as panning, tilting and zooming). Unlike some of the existing schemes, the proposed scheme is capable of detecting both sudden and gradual changes in uncompressed as well as compressed domain video. It is shown that the resultant motion vector can be used to identify and classify gradual changes due to camera movements. Results show that algorithm performed as well as the histogram-based schemes with uncompressed video. The performance of the algorithm was also investigated with H.263 compressed video. The detection and classification of both sudden and gradual scene changes was successfully demonstrated.
This paper presents a novel approach for videoretrieval from a large archive of MPEG or Motion JPEG(1) compressed video clips. We introduce a retrieval algorithm that takes a video clip as a query and searches the da...
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ISBN:
(纸本)0819424331
This paper presents a novel approach for videoretrieval from a large archive of MPEG or Motion JPEG(1) compressed video clips. We introduce a retrieval algorithm that takes a video clip as a query and searches the database for clips with similar contents. video clips are characterized by a sequence of representative frame signatures, which are constructed from DC coefficients and motion information (''DC+M'' signatures). The similarity between two video clips is determined by using their respective signatures. This method facilitates retrieval of clips for the purpose of video editing, broadcast news retrieval, or copyright violation detection.
A different approach to content-based retrieval and a novel framework for classification of visual information are proposed. The Visual Apprentice which is an implementation of the framework for still images and video...
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A different approach to content-based retrieval and a novel framework for classification of visual information are proposed. The Visual Apprentice which is an implementation of the framework for still images and video that uses a combination of lazy-learning, decision trees, and evolution programs for classification and grouping is introduced. Examples and results are given to demonstrate the applicability of the proposed approach to perform visual classification and detection.
We study the problem of retrieving images using a small template. The goal is to allow a user to search for images containing a pattern similar to the template, adding to the capability of a search engine. We propose ...
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ISBN:
(纸本)0819424331
We study the problem of retrieving images using a small template. The goal is to allow a user to search for images containing a pattern similar to the template, adding to the capability of a search engine. We propose to employ a segmentation-based approach. As a specific example, we introduce a quadtree segmentation technique for textured images and a distance measure, Sum of Minimum Distance, suitable for template-based imageretrieval applications.
In this paper, a novel visual search engine for videoretrieval and tracking from compressed multimedia databases is proposed. Our approach exploits the structure of video compression standards in order to perform obj...
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ISBN:
(纸本)0819429880
In this paper, a novel visual search engine for videoretrieval and tracking from compressed multimedia databases is proposed. Our approach exploits the structure of video compression standards in order to perform object matching directly on the compressed video data. This is achieved by utilizing motion compensation-a critical prediction filter embedded in video compression standards-to estimate and interpolate the desired method for template matching. Motion analysis is used to implement fast tracking of objects of interest on the compressed video data. Being presented with a query in the form of template images of objects, the system operates on the compressed video in order to find the images or video sequences where those objects are present and their positions in the image. This in turn enables the retrieval and display of the query-relevant sequences.
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