Flickr distance

Wu, Lei; Hua, Xian-Sheng; Yu, Nenghai; Ma, Wei‐Ying; Li, Shipeng

doi:10.1145/1459359.1459364

Cited by 142 publications

(65 citation statements)

References 18 publications

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“…On the other hand, several methods to measure distance (dis-similarity) between visual concepts have been proposed. Wu et al 133) proposed the Flickr distance, which is measured by the square root of JensenShannon (JS) divergence between the corresponding visual language models of two visual concepts. The latent topic based visual language models are learned with the images gathered from Flickr.…”

Section: Visual Concept Analysismentioning

confidence: 99%

[Invited Paper] A Review of Web Image Mining

Yanai

2015

MTA

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In this paper, we review works related to big visual data on the Web in the literature of computer vision and multimedia research regarding the following points: (1) Web image acquisition for construction of visual concept database for image/video recognition, (2) Web image application for visual concept analysis and data-driven computer graphics, and (3) real-world sensing through Web images to detect location-dependent and event-related visual information.

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Section: Visual Concept Analysismentioning

confidence: 99%

[Invited Paper] A Review of Web Image Mining

Yanai

2015

MTA

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“…Clements et al [56] used only geo-tags and proposed a weighting scheme, in order to identify similar places at world and city level. Wu et al [57] proposed Flickr distance, as a means of measuring relations between semantic concepts, construct a concept network and applied it to concept clustering and image annotation. A similar approach by Zhang et al [58] aimed to discover and visualize tag relationships from spatial and temporal similarities.…”

Section: Other Application Domainsmentioning

confidence: 99%

An Overview of Flickr Challenges and Research Opportunities

Spyrou

Mylonas

2014

2014 9th International Workshop on Semantic and Social Media Adaptation and Personalization

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Abstract-It is rather true that nowadays diversity and a potential for growth characterize the field of popular social networks like Flickr. Based on this observation, we provide herein a brief overview of the basic characteristics, challenges and research opportunities of the latter. Some historical facts of its origin are presented, followed by a review of its digital photo sharing and tagging capabilities, focusing on the most popular related research fields, like travel applications, knowledge extraction and human activity tracking. Throughout the paper the status of current research and directions for future research are highlighted in an effort to provide useful information to fellow researchers.

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“…[10] proposed an algorithm to integrate the visual similarity contexts between the images and the semantic similarity contexts between their tags for topic network generation. Flickr distance is proposed in [25], which is a novel measurement of the relationship between semantic concepts in visual domain. A visual concept network (VCNet) based on Flickr distance is also proposed [25].…”

Section: Related Workmentioning

confidence: 99%

“…Flickr distance is proposed in [25], which is a novel measurement of the relationship between semantic concepts in visual domain. A visual concept network (VCNet) based on Flickr distance is also proposed [25]. Semantic hierarchies have great potential to improve image annotation, particularly through their explicit representation of concepts relationships that may help to understand image semantics.…”

Section: Related Workmentioning

confidence: 99%

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Building Semantic Hierarchies Faithful to Image Semantics

Bannour

Hudelot

2012

Lecture Notes in Computer Science

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Abstract. This paper proposes a new image-semantic measure, named "Semantico-Visual Relatedness of Concepts" (SVRC ), to estimate the semantic similarity between concepts. The proposed measure incorporates visual, conceptual and contextual information to provide a measure which is more meaningful and more representative of image semantics. We also propose a new methodology to automatically build a semantic hierarchy suitable for the purpose of image annotation and/or classification. The building is based on the previously proposed measure SVRC and on a new heuristic, named TRUST-ME, to connect concepts with higher relatedness till the building of the final hierarchy. The built hierarchy explicitly encodes a general to specific concepts relationship and therefore provides a semantic structure to concepts which facilitates the semantic interpretation of images. Our experiments showed that the use of the constructed semantic hierarchies as a hierarchical classification framework provides a better image annotation.

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Flickr distance

Cited by 142 publications

References 18 publications

[Invited Paper] A Review of Web Image Mining

[Invited Paper] A Review of Web Image Mining

An Overview of Flickr Challenges and Research Opportunities

Building Semantic Hierarchies Faithful to Image Semantics

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