Search (7 results, page 1 of 1)

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Abstract

Semantic annotation of images is an important step to support semantic information extraction and retrieval. However, in a multi-annotator environment, various types of conflicts such as converting, merging, and inference conflicts could arise during the annotation. We devised conflict detection patterns based on different data, ontology at different inference levels and proposed the corresponding automatic conflict resolution strategies. We also constructed a simple annotator model to decide whether to trust a given piece of annotation from a given annotator. Finally, we conducted experiments to compare the performance of the automatic conflict resolution approaches during the annotation of images in the celebrity domain by 62 annotators. The experiments showed that the proposed method improved 3/4 annotation accuracy with respect to a naïve annotation system.

Source

Information processing and management. 42(2006) no.4, S.1030-1055

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Source

Information processing and management. 42(2006) no.3, S.723-728

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Source

Information processing and management. 42(2006) no.2, S.484-502

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Abstract

Web 2.0 and social/collaborative tagging have altered the traditional roles of indexer and user. Traditional indexing tools and systems assume the top-down approach to indexing in which a trained professional is responsible for assigning index terms to information sources with a potential user in mind. However, in today's Web, end users create, organize, index, and search for images and other information sources through social tagging and other collaborative activities. One of the impediments to user-centered indexing had been the cost of soliciting user-generated index terms or tags. Social tagging of images such as those on Flickr, an online photo management and sharing application, presents an opportunity that can be seized by designers of indexing tools and systems to bridge the semantic gap between indexer terms and user vocabularies. Empirical research on the differences and similarities between user-generated tags and index terms based on controlled vocabularies has the potential to inform future design of image indexing tools and systems. Toward this end, a random sample of Flickr images and the tags assigned to them were content analyzed and compared with another sample of index terms from a general image collection using established frameworks for image attributes and contents. The results show that there is a fundamental difference between the types of tags and types of index terms used. In light of this, implications for research into and design of user-centered image indexing tools and systems are discussed.

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Abstract

This paper discusses the goals and results of the research project Perseus-a as an attempt to improve information retrieval of digital images by automatically connecting them with text-based descriptions. The development uses the image collection of prometheus, the distributed digital image archive for research and studies, the articles of the digitized Reallexikon zur Deutschen Kunstgeschichte, art historical terminological resources and classification data, and an open source system for linguistic and statistic automatic indexing called lingo.

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Abstract

There are currently two dominant interface types for searching and browsing large image collections: keywordbased search, and searching by overall similarity to sample images. We present an alternative based on enabling users to navigate along conceptual dimensions that describe the images. The interface makes use of hierarchical faceted metadata and dynamically generated query previews. A usability study, in which 32 art history students explored a collection of 35,000 fine arts images, compares this approach to a standard image search interface. Despite the unfamiliarity and power of the interface (attributes that often lead to rejection of new search interfaces), the study results show that 90% of the participants preferred the metadata approach overall, 97% said that it helped them learn more about the collection, 75% found it more flexible, and 72% found it easier to use than a standard baseline system. These results indicate that a category-based approach is a successful way to provide access to image collections.

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Date

6. 1.2011 11:22:12