Veltkamp & Tanase (2000). Remco C. Veltkamp & Mirela Tanase, "Content-Based Image Retrieval Systems: A Survey," Technical Report, Dept. of Computing Science, Utrecht University.  Home/Search Document Details and Download
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Extracting Relational Facts for Indexing and Retrieval of .. - Pastra, Saggion, Wilks (2002) (2 citations) (Correct)
....research communities in this field focus on di#erent aspects of the images. The former focuses on the message to be conveyed and which is assigned by humans in the form of titles, captions or indexing terms, while the latter focuses on image attributes such as colour, texture and shape [17]. The problems with each approach are well known; visual attributes are not su#cient for image indexing and computer vision techniques are not that advanced yet to assist for this task. On the other hand, text based approaches carry all the problems encountered for decades in the traditional ....
R. Veltkamp and M. Tanase. Content-based image retrieval systems: a survey. Technical Report UU-CS-2000-34, Utrecht University, 2000.
An Attention Based Similarity Measure With Application to.. - Stentiford (2003) (4 citations) (Correct)
....visual material. Whilst storage and capture technologies are able to cope with the huge numbers of images, poor image retrieval is in danger of rendering many repositories valueless because of the difficulty of access. These problems have motivated much research into content based image retrieval [1,2,3,4] and many commercial and laboratory systems are described in the literature [5 12] It is the job of an image retrieval system to produce images that a user wants. In response to a user s query the system must offer images that are similar in some user defined sense. This goal is met by selecting ....
R. C. Veltkamp and M. Tanase, "Content-based image retrieval systems: a survey," March 2001, http://www.aa-lab.cs.uu.nl/cbirsurvey/cbir-survey/.
RETIN: A content-based image indexing and retrieval system - Fournier, Cord.. (2001) (Correct)
....[7] The other approach is called target search. The problem is to lead the system to the target image by validating a displayed set of images (see [8] 9] 10] The aim of this section is not to make an exhaustive survey of the existing systems in CBIR (the interested reader can refer to [11]) but rather to give a few details about the main references of our work. One of the most exhaustive works on image similarities is presented by Nastar et al. and synthesized in the search engine named Surfimage (see [3] This system is generic and based on pre attentive similarities between ....
R.C. Veltkamp and M. Tanase. Content-based image retrieval systems : A survey. Technical report UU-CS-2000-34, Department of Computing Science, Utrecht University, October 2000. 34
Content-Based Image Retrieval Systems - Stanchev (2001) (1 citation) (Correct)
....24. WebSEEk. Developer Image and Advanced Television Lab, Columbia University, NY. URL http: www.ctr.columbia.edu VVebSEEk . CONCLUSIONS Most content based image retrieval systems are products of research, and therefore emphasize one aspect of content based retrieval [23]. Most systems use color and texture features, few systems use shape feature, and still less use spatial features. The retrieval on color usually yields images with similar colors. Retrieval on texture does not always yield images that have clearly the same texture, unless the database contains ....
Veltkamp, R. and Tanase, M., Content-Based Image Retrieval Systems: A Survey, Department of Computing Science, Utrecht University, working material (2000).
Web-Based User Interface For Query Specification In A Video.. - Saykol (2001) (6 citations) (Correct)
....thesis. Chapter 2 Related Work 2. 1 Content Based Retrieval Systems There exist quite a number of content based retrieval (CBR) systems in the literature: QBIC [15] VisualSEEk [42] VideoQ [7] Photobook [32] ImageRover [38] Surfimage [29] Detailed surveys on CBR systems are available in [46] and [48] In most of these systems, color is a must object feature for the retrieval process. However, some of the systems allowing color queries do not develop new techniques for color but in other areas such as spatio temporal relations. Section 5.1 presents a detailed summary on color and ....
R.C. Veltkamp, M. Tanase. Content-Based Image Retrieval Systems: A Survey. Technical Report UU-CS-
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Veltkamp & Tanase (2000). Remco C. Veltkamp & Mirela Tanase, "Content-Based Image Retrieval Systems: A Survey," Technical Report, Dept. of Computing Science, Utrecht University.
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Veltkamp, R.C., Tanase M.: Content-Based Image Retrieval Systems: A Survey. (Technical Report UU-CS-2000-34). Institute of Information and Computing Sciences, Univ. of Utrecht, The Netherlands (2000)
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R. C. Veltkamp and M. Tanase, "Content-Based Image Retrieval Systems: A Survey," Univ. Utrecht, Utrecht, The Netherlands, Tech. Rep. UU-CS-2000-34. [Online] Available: http://ftp.cs.ruu.nl/research/ techreps/aut/remcov.html.
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Veltkamp, R. C., Tanase, M., Content-based image retrieval systems: a survey. March 2001, http://www.aa-lab.cs.uu.nl/cbirsurvey/cbir-survey/.
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R.C. Veltkamp, "Content-based image retrieval system: A survey," Tech. Rep., University of Utrecht, 2002.
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R.C. Veltkamp, "Content-based image retrieval system: A survey," Tech. Rep., University of Utrecht, 2000.
Extracting Relational Facts for Indexing and Retrieval of .. - Pastra, Saggion, Wilks (2003) (2 citations) (Correct)
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R. Veltkamp, M. Tanase, Content-based image retrieval systems: a survey, Technical Report UU-CS-2000-34, Utrecht University, 2000.
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R. Veltkamp and M. Tanase. Content-based image retrieval systems: A survey. Technical Report UU-CS-2000-34, Universiteit Utrecht Institute of Information And Computing Sciences, 2000.
A 3D Model Search Engine - Min (2004) (Correct)
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R. C. Veltkamp and M. Tanase. Content-based image retrieval systems: A survey. Technical Report UU-CS-2000-34, Utrecht University, October 2000.
Region-Based Image Retrieval Using Integrated Color, Shape .. - Prasad, Biswas, Gupta (2003) (Correct)
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R.C. Veltkamp and M. Tanase, Content-Based Image Retrieval Systems: A Survey, UU-CS-2000-34, Department of Computer Science, Utretch University, October, (2002).
Image Retrieval Using Natural Language and Content-Based.. - Byrne, Klein (2003) (Correct)
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R. C. Veltkamp and M. Tanase. Content-based image retrieval systems: a survey. Technical Report UU-CS-2000-34, Utrecht University, Department of Computing Science, October 2000.
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R. C. Veltkamp and M. Tanase. Content-Based Image Retrieval Systems: A Survey. Technical Report UU-CS-200034, Dept. of Computing Science, Utrecht University, 2000.
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