Visual information retrieval from large distributed online repositories

Chang, Shih‐Fu; Smith, J. R.; Beigi, Mandis; Benitez, Ana B.

doi:10.1145/265563.265573

Cited by 160 publications

(68 citation statements)

References 6 publications

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“…The incapacity of the query-by-example (QBE) paradigm to support semantic queries is a well known fact in the literature of CBR [3]- [5]. The operationalization of CBR based on the QBE paradigm has been popularly used to serve the perceptual similarity search such as for finding copies and variants of an artwork for which an example is available at hand.…”

Section: B Incapacity Of the Qbe Paradigmmentioning

confidence: 99%

Retrieval For Color Artistry Concepts

Lay

Guan

2004

IEEE Trans. on Image Process.

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Abstract-This paper presents a work on the retrieval of artworks for color artistry concepts. First we affirm the view that the Query-by-Example paradigm fundamental to the current content-based retrieval systems is able to extend only limited usefulness. We then propose a concept-based retrieval engine based on the generative grammar of elemental concepts methodology. In the latter, the language by which color artistry concepts are communicated in artworks is used to operate semantic searches. The color artistry language is explicated into elemental concepts and the associated generative grammar. The elemental concepts are used to index the artworks, while the generative grammar is used to facilitate post-coordinate expression of color artistry concept queries by using the elemental concepts.Index Terms-Color artistry concepts, concept-based retrieval, generative grammar of elecepts.

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Section: B Incapacity Of the Qbe Paradigmmentioning

confidence: 99%

Retrieval For Color Artistry Concepts

Lay

Guan

2004

IEEE Trans. on Image Process.

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“…CHIIR '17 March 07-11, 2017, Oslo, Norway of finding the proper scene of interest in a large video archive (e.g., [1,4,5,6,11,16,17,20,22,25,15]). Video retrieval tools use content-based indexing methods to perform automatic annotation with content descriptors for color, texture, shape, and semantic concepts.…”

Section: Interactive Video Searchmentioning

confidence: 99%

Interactive Search in Video & Lifelogging Repositories

Hopfgartner

Schoeffmann

2017

Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval

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Due to increasing possibilities to create digital video, we are facing the emergence of large video archives that are made accessible either online or offline. Though a lot of research has been spent on video retrieval tools and methods, which allow for automatic search in videos, still the performance of automatic video retrieval is far from optimal.At the same time, the organization of personal data is receiving increasing research attention due to the challenges that are faced in gathering, enriching, searching and visualizing this data. Given the increasing quantities of personal data being gathered by individuals, the concept of a heterogeneous personal digital libraries of rich multimedia and sensory content for every individual is becoming a reality.Despite the differences between video archives and personal lifelogging libraries, we are facing very similar challenges when accessing these multimedia repositories. For example, users will struggle to find the information they are looking for in either collection if they are not able to formulate their search needs through a query. In this tutorial we discussed (i) proposed solutions for improved video & lifelog content navigation, (ii) typical interaction of content-based querying features, and (iii) advanced content visualization methods. Moreover, we discussed and demonstrate interactive video & lifelog search systems and ways to evaluate their performance.

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“…If not, we could still get similar information on the basis of the text surrounding the multimedia documents [5]. Our system could be easily adopted to produce multimedia document type feature vector based on the annotation information and facilitate the multimedia document search.…”

Section: Final Remarksmentioning

confidence: 99%

Discovering Document Semantics QBYS: A System for Querying the WWW by Semantics

Johnson

Fotouhi

Drăghici

et al. 2004

Multimedia Tools and Applications

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Abstract. This paper describes our research into a query-by-semantics approach to searching the World Wide Web. This research extends existing work, which had focused on a query-by-structure approach for the Web. We present a system that allows users to request documents containing not only specific content information, but also to specify that documents be of a certain type. The system captures and utilizes structure information as well as content during a distributed query of the Web. The system also allows the user the option of creating their own document types by providing the system with example documents. In addition, although the system still gives users the option of dynamically querying the web, the incorporation of a document database has improved the response time involved in the search process. Based on extensive testing and validation presented herein, it is clear that a system that incorporates structure and document semantic information into the query process can significantly improve search results over the standard keyword search.

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Visual information retrieval from large distributed online repositories

Cited by 160 publications

References 6 publications

Retrieval For Color Artistry Concepts

Retrieval For Color Artistry Concepts

Interactive Search in Video & Lifelogging Repositories

Discovering Document Semantics QBYS: A System for Querying the WWW by Semantics

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