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Texture content based retrieval using text descriptions

Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 75-85页

作者： Kuan, J.K.P. Joyce, D.W. Lewis, P.H. ADC Metrica Richmond United Kingdom

We developed a content based retrieval scheme for texture by using text based description. The texture technique is based on our previous work which uses very simple texture primitives such as edges and plain regions to generate features. Other methods that apply complicated statistics can be difficult to transcribe into understandable forms for normal users. Unlike these other methods, with the simplicity of our features, we can express them in terms of simple language. Hence we can bridge the gap between semantics and computed features. A number of benefits can be achieved which opens a new horizon for content based retrieval with texture. For example, the user can request a texture image without necessarily knowing what types of textures are stored. In this paper we describe the method of translating such features and the partial weighted Euclidean distance matching which allows users to describe only the parts that they are interested in. This allows them to gradually refine their texture descriptions.

关键词： Information retrieval

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Gesture for video content navigation

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 230-242页

作者： Bradski, Gary Yeo, Boon-Lock Yeung, Minerva M. Intel Corp Santa Clara United States

This article describes the use of gesture recognition techniques in computer vision as a natural interface for video content navigation, and the design of a navigation and browsing system that caters to these natural means of computer-human interaction. For consumer applications, video content navigation presents two challenges: (1) how to parse and summarize multiple video streams in an intuitive and efficient manner, and (2) what type of interface will enhance the ease of use for video browsing and navigation in a living room setting or an interactive environment. In this paper, we address the issues and propose the techniques that combine video content navigation with gestures, seamlessly and intuitively, in an integrated system. The current framework can incorporate speech recognition technology. We present a new type of browser for browsing and navigating video content, as well as a gesture recognition interface for this browser.

关键词： Pattern recognition

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New anchor selection methods for image retrieval

New anchor selection methods for image retrieval

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conference on storage and retrieval for Media databases 2003

作者： Natsev, A Smith, JR IBM Corp TJ Watson Res Ctr Hawthorne NY 10532 USA

ISBN: (纸本)0819448214

Anchoring is a technique for representing objects by their distances to a few well chosen landmarks, or anchors. Objects are mapped to distance-based feature vectors, which can be used for content-based retrieval, classification, clustering, and relevance feedback of images, audio, and video. The anchoring transformation typically reduces dimensionality and replaces expensive similarity computations in the original domain with simple distance computations in the anchored feature domain, while guaranteeing lack of false dismissals. Anchoring is therefore surprisingly simple, yet effective, and flavors of it have seen application in speech recognition, audio classification, protein homology detection, and shape matching. In this paper, we describe the anchoring technique in some detail and study methods for anchor selection, both from an analytical, as well as empirical, standpoint. Most work to date has largely ignored this problem by fixing the anchors to be the entire set of objects or by using greedy selection from among the set of objects. We generalize previous work by considering anchors from outside of the object space, and by deriving an analytical upper bound on the distance-approximation error of the method.

关键词： image retrieval databases Error analysis Feature extraction Vector spaces video image classification Proteins Transform theory Visualization

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Semi-automatic dynamic video object marker creation

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 178-185页

作者： Toklu, Candemir Liou, Shih-Ping Siemens Corporate Research Inc Princeton United States

In this paper we propose a method for tracking a video object in an ordered sequence of two-dimensional images, where the outcome is the trajectory of the video object throughout the time sequence of images. This method is designed to run in real-time in a synchronous video collaboration environment, and used for producing dynamic object annotations for enhanced video content understanding. A dynamic object is an object whose location or size in the video frame constantly changes due to the camera motion, the motion of its own, or both. We suggest a novel method for finding the trajectory of the object in the intermediate frames given the locations and shapes of the object in two end frames. In addition to the shape and location information of the object, its texture information in the end frames is used to predict the location and search space of it in the intermediate frames.

关键词： Object recognition

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Vector angular distance measure for indexing and retrieval of color

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 604-613页

作者： Androutsos, D. Plataniotis, K.N. Venetsanopoulos, A.N. Univ of Toronto Toronto Canada

A key aspect of image retrieval 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.

关键词： Color image processing

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Rotation, translation, and scaling invariant color image indexing

Rotation, translation, and scaling invariant color image ind...

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7th storage and retrieval for image and video databases conference

作者： Celenk, M Shao, Y Ohio Univ Sch Elect Engn & Comp Sci Athens OH 45701 USA

ISBN: (纸本)0819431273

This paper describes a rotation, translation, and scaling (RTS) invariant color image indexing technique for imaging database systems. The features used for image indexing are color based, which are extracted using the principal component analysis, Hotelling transform, and moment invariants. This synthesized feature extraction technique is devised to be computationally efficient for on-line fast image storage and retrieval using color information Since the database indexing relies on a the use of average (mean) color vector and seven moment invariants of an image, the index storage requirement of the method is only a ten-dimensional (10-D) vector. This index storage efficiency is very desirable for many imaging database applications. A new similarity measure is also proposed based on the Tanimoto measure of recognizing similar patterns for fast image retrieval in large database systems. The underlying similarity measure is computationally effective since the vector inner product is the only operation needed for its computation. Four databases are experimented in the computer simulation of the algorithm to demonstrate the RTS property of the image retrieval. It is determined experimentally that the proposed method is not affected by substantial changes in the database images due to rotation, translation, and scaling. This is attributed to the fact that the moment features used for retrieval are not predefined sets;rather, they are obtained directly from the images submitted for recording or searching. This makes the algorithm very robust and attractive for many applications of the image storage and retrieval systems.

关键词： color image storage and retrieval principal components Hotelling transform moment invariants Tanimoto measure

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Segmentation based image retrieval

Segmentation based image retrieval

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storage and retrieval for image and video databases VI conference

作者： Siebert, A Univ British Columbia Dept Comp Sci Vancouver BC V6T 1W5 Canada

ISBN: (纸本)0819427527

We have been developing an image retrieval system, called MIPS (Multiscalar image Processing and retrieval System), for use in uncontrolled environments. On insertion into the image database, the images are automatically segmented into homogeneous regions. Generic features are computed and stored for each segment. Specifically, we maintain not only geometric and photometric attributes but also simple spatial information for each extracted region. This approach asks the user to construct queries in terms of the given primitives, i.e. regions and their spatial relations. Preliminary results show that the success of the system depends on how well the images can be modelled by homogeneous regions, on how useful the generic features are for the given application, and on the knowledge that the user puts into the formulation of the queries. A fully automatic segmentation algorithm is of paramount importance. We have designed an algorithm called Perceptual Region Growing that combines region growing, edge detection, and perceptual organization principles, without resorting to any kind of high level knowledge or interactive user intervention. Decision thresholds and quality measures are directly derived from the image data, based on image statistics. Search through critical parameter spaces is the key idea to cope with noise in uncontrolled environments. The dynamics of the region growing process is constantly monitored and exploited.

关键词： image retrieval segmentation region growing

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引用

7th storage and retrieval for image and video databases conference

作者： Chen, KS Demko, S Xie, RF Iterated Syst Inc Piedmont Ctr 7 Atlanta GA 30305 USA

ISBN: (纸本)0819431273

The color histogram 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 the 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.

关键词： image database content-based image retrieval image descriptor perceptual similarity color histogramming distance metric

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Models for automatic classification of video sequences

Models for automatic classification of video sequences

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storage and retrieval for image and video databases VI conference

作者： Iyengar, G Lippman, A MIT Media Lab Cambridge MA 02139 USA

ISBN: (纸本)0819427527

In this paper, we explore a technique for automatic classification of video sequences, (such as a TV broadcast, movies). This technique analyses the incoming video sequences and classifies them into categories. It can be viewed as an on-line parser for video signals. We present two techniques for automatic classification. In the first technique, the incoming video sequence is analyzed to extract the motion information. This information is optimally projected onto a single dimension. This projection information is then used to train Hidden Markov Models (HMMs) that efficiently and accurately classify the incoming video sequence. Preliminary results with 50 different test sequences (25 Sports and 25 News sequences) indicate a classification accuracy of 90% by the HMM models. In the second technique, 24 full length motion picture trailers are classified using HMMs. This classification is compared with the internet movie database and we find that they correlate well. Only two out of 24 trailers were classified incorrectly.

关键词： Hidden Markov Models video characterization and classification video indexing automatic content screening density estimation learning

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A novel approach to scene change detection using a cross entropy

A novel approach to scene change detection using a cross ent...

引用

IEEE International conference on image Processing (ICIP 2000)

作者： Kim, SH Park, RH Sogang Univ Dept Elect Engn Seoul 100611 South Korea

ISBN: (纸本)0780362985

In huge video databases, the effective video indexing method is required. While manual indexing is the most effective approach to this goal, it is slow and expensive. Thus automatic indexing is desirable and recently various indexing tools for video databases have been developed. For efficient video indexing and retrieval, the similarity measure is an important factor. This paper presents new similarity measures between frames and proposes a new algorithm to detect scene changes using a cross entropy defined between two histograms. Experimental results show that the proposed algorithm is fast and effective compared with several conventional algorithms to detect abrupt scene changes and gradual transitions including fade in/out and flash light scenes.

关键词： video signal processing

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