We have witnessed great interest and a wealth of promise in content-based image retrieval as an emerging technology. While the last decade laid foundation to such promise, it also paved the way for a large number of new techniques and systems, got many new people involved, and triggered stronger association of weakly related fields. In this article, we survey almost 300 key theoretical and empirical contributions in the current decade related to image retrieval and automatic image annotation, and in the process discuss the spawning of related subfields. We also discuss significant challenges involved in the adaptation of existing image retrieval techniques to build systems that can be useful in the real world. In retrospect of what has been achieved so far, we also conjecture what the future may hold for image retrieval research.

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Image retrieval: Ideas, influences, and trends of the new age

We present here SIMPLIcity (semantics-sensitive integrated matching for picture libraries), an image retrieval system, which uses semantics classification methods, a wavelet-based approach for feature extraction, and integrated region matching based upon image segmentation. An image is represented by a set of regions, roughly corresponding to objects, which are characterized by color, texture, shape, and location. The system classifies images into semantic categories. Potentially, the categorization enhances retrieval by permitting semantically-adaptive searching methods and narrowing down the searching range in a database. A measure for the overall similarity between images is developed using a region-matching scheme that integrates properties of all the regions in the images. The application of SIMPLIcity to several databases has demonstrated that our system performs significantly better and faster than existing ones. The system is fairly robust to image alterations.

/pdf/simplicity-semantics-sensitive-integrated-matching-for-3bfwe17qcj.pdf

SIMPLIcity: semantics-sensitive integrated matching for picture libraries

Adaptive hypermedia is a relatively new direction of research on the crossroads of hypermedia and user modeling. Adaptive hypermedia systems build a model of the goals, preferences and knowledge of each individual user, and use this model throughout the interaction with the user, in order to adapt to the needs of that user. The goal of this paper is to present the state of the art in adaptive hypermedia at the eve of the year 2000, and to highlight some prospects for the future. This paper attempts to serve both the newcomers and the experts in the area of adaptive hypermedia by building on an earlier comprehensive review (Brusilovsky, 1996; Brusilovsky, 1998).

Adaptive Hypermedia

We present here SIMPLIcity (Semantics-sensitive Integrated Matching for Picture LIbraries), an image retrieval system using semantics classification and integrated region matching (IRM) based upon image segmentation. The SIMPLIcity system represents an image by a set of regions, roughly corresponding to objects, which are characterized by color, texture, shape, and location. The system classifies images into categories which are intended to distinguish semantically meaningful differences, such as textured versus nontextured, indoor versus outdoor, and graph versus photograph. Retrieval is enhanced by narrowing down the searching range in a database to a particular category and exploiting semantically-adaptive searching methods. A measure for the overall similarity between images, the IRM distance, is defined by a region-matching scheme that integrates properties of all the regions in the images. This overall similarity approach reduces the adverse effect of inaccurate segmentation, helps to clarify the semantics of a particular region, and enables a simple querying interface for region-based image retrieval systems. The application of SIMPLIcity to a database of about 200,000 general-purpose images demonstrates accurate retrieval at high speed. The system is also robust to image alterations.

/pdf/simplicity-semantics-sensitive-integrated-matching-for-24qhzda1r8.pdf

SIMPLIcity: Semantics-sensitive Integrated Matching for Picture Libraries

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Multivariate Data Analysis With Readings

A method and apparatus for providing a user interface for refining a query applied to a database of images, where a Query Result Visualization Environment allows the user to organize the search results using various techniques. For example, the search results may be clustered on the basis of text, image or URL. The members of the resulting clusters may then be utilized by the user to refine the query to be applied to the database of images.

Method and apparatus for query refinement

Search engines are useful because they allow the user to find information of interest from the World Wide Web. However, most of the popular search engines today are textuals they do not allow the user to find images from the Web. This paper describes AMORE, a Web search engine that allows the user to retrieve images from the Web by specifying relevant keywords or a similar image. Text and image search can also be combined. Moreover, we have developed a Query Result Visualization Environment that allows the organization of the results if many images are retrieved. In this paper we present AMORE’s user interface and explain the technique for retrieving images visually similar to a user specified image. The method of automatically assigning relevant keywords to the images is then explained. Finally, the architecture of the system as well as some interesting observations of our experiences with AMORE are discussed.

AMORE: A World Wide Web image retrieval engine

Users of the Web are overloaded with information. This medium is “polluted” with redundant, erroneous and low quality information. A WWW survey of 11,700 users conducted from April 10 to May 10, 1996[1] indicates that 30.31% of the users report “finding known info” is their problem and 27.80% of the users report organizing collected information as their problem. An empirical study[2] on users’ revisitation patterns to WWW pages found that 58% of an individual’s pages are revisits. With these study results, we believe the Web users would like to build and organize a larger collection of bookmarks for future references than they can reasonably maintain now.

PowerBookmarks: a system for personalizable Web information organization, sharing, and management

We extend the notion of bookmark management by introducing the functionalities of hypermedia databases. PowerBookmarks is a Web information organization, sharing, and management tool, which parses metadata from bookmarked URLs and uses it to index and classify the URLs. PowerBookmarks supports advanced query, classification, and navigation functionalities on collections of bookmarks. PowerBookmarks monitors and utilizes users' access patterns to provide many useful personalized services, such as automated URL bookmarking, document refreshing, and bookmark expiration. It also allows users to specify their preference in bookmark management, such as ranking schemes and classification tree structures. Subscription services for new or updated documents of users' interests are also supported.

With the explosive growth of information that is available on the World-Wide Web, it is very easy for the user to get lost in hyperspace. When the user feels lost, some idea of the position of the current node in the overall information space will help to orient the user. Therefore we have developed a technique to form focus+context views of WorldWide Web nodes. The view shows the immediate neighborhood of the current node and its position with respect to the important (landmark) nodes in the information space. The views have been used to enhance a Web search engine. We have also used the landmark nodes and the focus+ context views in forming overview diagrams of Web sites.

Yoshinori Hara

Papers

Method and apparatus for query refinement

AMORE: A World Wide Web image retrieval engine

PowerBookmarks: a system for personalizable Web information organization, sharing, and management

PowerBookmarks: a system for personalizable Web information organization, sharing, and management

Focus+context views of World-Wide Web nodes