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P. Pala - One of the best experts on this subject based on the ideXlab platform.

  • Content Based Retrieval of 3d models
    ACM Transactions on Multimedia Computing Communications and Applications, 2006
    Co-Authors: Alberto Del Bimbo, P. Pala
    Abstract:

    In the past few years, there has been an increasing availability of technologies for the acquisition of digital 3D models of real objects and the consequent use of these models in a variety of applications, in medicine, engineering, and cultural heritage. In this framework, Content-Based Retrieval of 3D objects is becoming an important subject of research, and finding adequate descriptors to capture global or local characteristics of the shape has become one of the main investigation goals. In this article, we present a comparative analysis of a few different solutions for description and Retrieval by similarity of 3D models that are representative of the principal classes of approaches proposed. We have developed an experimental analysis by comparing these methods according to their robustness to deformations, the ability to capture an object's structural complexity, and the resolution at which models are considered.

  • 3D Content-Based Retrieval with spin images
    2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), 2004
    Co-Authors: J. Assfalg, G. D'amico, A. Del Bimbo, P. Pala
    Abstract:

    Along with images and videos, 3D models have recently gained increasing attention for a number of reasons: advancements in 3D hardware and software technologies; their ever decreasing prices and increasing availability; affordable 3D authoring tools; the establishment of open standards for 3D data interchange. The ever increasing availability of 3D models demands tools to support their effective and efficient management. Among these tools, those enabling Content-Based Retrieval play a key role. We present a novel approach to 3D Content-Based Retrieval that is Based on spin images. Spin images are used to derive a view-independent description of both database and query objects: a set of spin images is first created for each object; then, a descriptor is evaluated for each spin image in the set; clustering is performed on the set of image-Based descriptors of each object to achieve a compact representation of the object, thus allowing for efficient indexing and matching. Experimental results are presented for a test database of about 300 models. These results indicate that spin images can be successfully exploited for Content-Based Retrieval of 3D objects

  • ICME - 3D Content-Based Retrieval with spin images
    2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), 2004
    Co-Authors: J. Assfalg, G. D'amico, A. Del Bimbo, P. Pala
    Abstract:

    Along with images and videos, 3D models have recently gained increasing attention for a number of reasons: advancements in 3D hardware and software technologies; their ever decreasing prices and increasing availability; affordable 3D authoring tools; the establishment of open standards for 3D data interchange. The ever increasing availability of 3D models demands tools to support their effective and efficient management. Among these tools, those enabling Content-Based Retrieval play a key role. We present a novel approach to 3D Content-Based Retrieval that is Based on spin images. Spin images are used to derive a view-independent description of both database and query objects: a set of spin images is first created for each object; then, a descriptor is evaluated for each spin image in the set; clustering is performed on the set of image-Based descriptors of each object to achieve a compact representation of the object, thus allowing for efficient indexing and matching. Experimental results are presented for a test database of about 300 models. These results indicate that spin images can be successfully exploited for Content-Based Retrieval of 3D objects

T. Ichikawa - One of the best experts on this subject based on the ideXlab platform.

  • A survey on Content-Based Retrieval for multimedia databases
    IEEE Transactions on Knowledge and Data Engineering, 1999
    Co-Authors: A. Yoshitaka, T. Ichikawa
    Abstract:

    Conventional database systems are designed for managing textual and numerical data, and retrieving such data is often Based on simple comparisons of text/numerical values. However, this simple method of Retrieval is no longer adequate for multimedia data, since the digitized representation of images, video, or data itself does not convey the reality of these media items. In addition, composite data consisting of heterogeneous types of data also associates with the semantic Content acquired by a user's recognition. Therefore, Content-Based Retrieval for multimedia data is realized taking such intrinsic features of multimedia data into account. Implementation of the Content-Based Retrieval facility is not Based on a single fundamental, but is closely related to an underlying data model, a priori knowledge of the area of interest, and the scheme for representing queries. This paper surveys recent studies on Content-Based Retrieval for multimedia databases from the point of view of three fundamental issues. Throughout the discussion, we assume databases that manage only nontextual/numerical data, such as image or video, are also in the category of multimedia databases.

  • Knowledge-assisted Content Based Retrieval for multimedia databases
    IEEE MultiMedia, 1994
    Co-Authors: A. Yoshitaka, S. Kishida, Masahito Hirakawa, T. Ichikawa
    Abstract:

    Unlike conventional databases, which manage only text and numerical data, multimedia databases must evaluate audio and visual properties of data. We propose a system of querying and Content-Based Retrieval that considers audio or visual properties of multimedia data. >

J. Assfalg - One of the best experts on this subject based on the ideXlab platform.

  • 3D Content-Based Retrieval with spin images
    2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), 2004
    Co-Authors: J. Assfalg, G. D'amico, A. Del Bimbo, P. Pala
    Abstract:

    Along with images and videos, 3D models have recently gained increasing attention for a number of reasons: advancements in 3D hardware and software technologies; their ever decreasing prices and increasing availability; affordable 3D authoring tools; the establishment of open standards for 3D data interchange. The ever increasing availability of 3D models demands tools to support their effective and efficient management. Among these tools, those enabling Content-Based Retrieval play a key role. We present a novel approach to 3D Content-Based Retrieval that is Based on spin images. Spin images are used to derive a view-independent description of both database and query objects: a set of spin images is first created for each object; then, a descriptor is evaluated for each spin image in the set; clustering is performed on the set of image-Based descriptors of each object to achieve a compact representation of the object, thus allowing for efficient indexing and matching. Experimental results are presented for a test database of about 300 models. These results indicate that spin images can be successfully exploited for Content-Based Retrieval of 3D objects

  • ICME - 3D Content-Based Retrieval with spin images
    2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), 2004
    Co-Authors: J. Assfalg, G. D'amico, A. Del Bimbo, P. Pala
    Abstract:

    Along with images and videos, 3D models have recently gained increasing attention for a number of reasons: advancements in 3D hardware and software technologies; their ever decreasing prices and increasing availability; affordable 3D authoring tools; the establishment of open standards for 3D data interchange. The ever increasing availability of 3D models demands tools to support their effective and efficient management. Among these tools, those enabling Content-Based Retrieval play a key role. We present a novel approach to 3D Content-Based Retrieval that is Based on spin images. Spin images are used to derive a view-independent description of both database and query objects: a set of spin images is first created for each object; then, a descriptor is evaluated for each spin image in the set; clustering is performed on the set of image-Based descriptors of each object to achieve a compact representation of the object, thus allowing for efficient indexing and matching. Experimental results are presented for a test database of about 300 models. These results indicate that spin images can be successfully exploited for Content-Based Retrieval of 3D objects

Jae Woo Chang - One of the best experts on this subject based on the ideXlab platform.

  • Structure- and Content-Based Retrieval for XML Documents
    Human Computer Interaction, 2020
    Co-Authors: Jae Woo Chang
    Abstract:

    As the number of XML documents is dramatically increasing, it is necessary to develop an XML document Retrieval system that can support both structure-Based Retrieval and Content-Based Retrieval. In order to support the structure-Based Retrieval, we design four efficient index structures, i.e., keyword, structure, element and attribute index, by indexing XML documents Based on a basic element unit. In order to support the Content-Based Retrieval, we design a high-dimensional index structure Based on the X-tree so as to store and retrieve both color and shape feature vectors efficiently. Finally, we do the performance evaluation of our XML document Retrieval system in terms of system efficiency, such as Retrieval time, insertion time, and storage overhead, as well as system effectiveness, such as recall and precision measures.

  • A Multimedia Document Retrieval System Supporting Structure- and Content-Based Retrieval
    Interactive Multimedia Systems, 2020
    Co-Authors: Jae Woo Chang
    Abstract:

    Recently it is common for users to acquire through the World Wide Web a variety of multimedia documents. As the number of Web documents is dramatically increasing, we need to develop a multimedia document Retrieval system that can support both structure-Based Retrieval and Content-Based Retrieval. In order to support structure-Based Retrieval, we design efficient index structures (i.e., keyword, structure, element and attribute) and implement those by using the o2store storage system. For the Content-Based Retrieval, we implement high-dimensional index structure for color and shape feature that is Based on X-tree. Finally, we do the performance evaluation of our multimedia document Retrieval system in terms of system efficiency, such as Retrieval time, insertion time and storage overhead, as well as system effectiveness, such as recall and precision measures.

  • Structure- and Content-Based Retrieval for XML documents
    Human-Computer Interaction, 2020
    Co-Authors: Jae Woo Chang
    Abstract:

    As the number of XML documents is dramatically increasing, it is necessary to develop an XML document Retrieval system that can support both structureBased Retrieval and Content-Based Retrieval. In order to support the structureBased Retrieval, we design four efficient index structures, i.e., keyword, structure, element and attribute index, by indexing XML documents Based on a basic element unit. In order to support the Content-Based Retrieval, we design a highdimensional index structure Based on the X-tree so as to store and retrieve both color and shape feature vectors efficiently. Finally, we do the performance evaluation of our XML document Retrieval system in terms of system efficiency, such as Retrieval time, insertion time, and storage overhead, as well as system effectiveness, such as recall and precision measures. INTRODUCTION The XML (eXtensible Markup Language) was proposed as a standard markup language to make Web documents in 1996[W3C, 2000]. It has as good expressive power as SGML and is also easy to use like HTML. Recently, it has been common for users to acquire through the Web a variety of multimedia documents written by XML. Meanwhile, because the number of XML documents is dramatically increasing, it is difficult to reach a specific XML document required by users. Moreover, an XML document not only has a logical and hierarchical structure commonly, but also contains its multimedia data, such as image and video. Thus, it is necessary to develop an XML document Retrieval system that can support both the Retrieval Based on document structure and the Retrieval Based on image Content. In general, since the conventional XML document Retrieval systems support only structure-Based Retrieval, it is impossible to deal with a user query which requires both structureand Content-Based Retrieval for XML document. In this chapter, we design and implement an XML document Retrieval system that can efficiently retrieve XML documents Based on both document structure and image Content. In order to support the structure-Based Retrieval, we design four efficient index structures, i.e., keyword, structure, element and attribute index, by indexing XML documents Based on a basic element unit and implement This chapter appears in the book, Human Computer Interaction: Issues and Challenges by Qiyang Chen. Copyright © 2001, Idea Group Publishing. 701 E. Chocolate Avenue, Hershey PA 17033-1117, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.idea-group.com ITB7973 IDEA GROUP PUBLISHING

A.e. Cetin - One of the best experts on this subject based on the ideXlab platform.

  • Content-Based Retrieval of historical Ottoman documents stored as textual images
    IEEE Transactions on Image Processing, 2004
    Co-Authors: E. Saykol, A.k. Sinop, U. Gudukbay, O. Ulusoy, A.e. Cetin
    Abstract:

    There is an accelerating demand to access the visual Content of documents stored in historical and cultural archives. Availability of electronic imaging tools and effective image processing techniques makes it feasible to process the multimedia data in large databases. A framework for Content-Based Retrieval of historical documents in the Ottoman Empire archives is presented. The documents are stored as textual images, which are compressed by constructing a library of symbols occurring in a document, and the symbols in the original image are then replaced with pointers into the codebook to obtain a compressed representation of the image. The features in wavelet and spatial domains, Based on angular and distance span of shapes, are used to extract the symbols. In order to make Content-Based Retrieval in the historical archives, a query is specified as a rectangular region in an input image and the same symbol-extraction process is applied to the query region. The queries are processed on the codebook of documents and the query images are identified in the resulting documents using the pointers in the textual images. The query process does not require decompression of images. The new Content-Based Retrieval framework is also applicable to many other document archives using different scripts.