Directing your own live and interactive sports channel

Poslad, Stefan; Pnevmatikakis, Aristodemos; Nunes, Mário Serafim; Ostermann, Elena Garrido; Chippendale, Paul; Brightwell, Peter; Patrikakis, Charalampos Z.

doi:10.1109/wiamis.2009.5031486

Cited by 5 publications

(3 citation statements)

References 10 publications

(7 reference statements)

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“…Knowledge deployment applies the Ontology model in order to support semantic queries on image captions. Again there are several sub-processes involved: eliminating stop words within captions, automatically formulating queries to be represented as SPARQL queries 1 and compensating for missing concepts in the image caption. The SPARQL query performs a semantic search on the RDF file and returns results to a user.…”

Section: Proposed Frameworkmentioning

confidence: 99%

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Semantic Restructuring of Natural Language Image Captions to Enhance Image Retrieval

Kesorn¹,

Poslad²

2009

JMM

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The rapid growth in the volume of visual information can make the task of finding and accessing visual information of interest, overwhelming for users. Semantic analysis of image captions can be used in conjunction with image retrieval systems (IMR) to retrieve selected images more precisely. To do this, we first exploit a Natural Language Processing (NLP) framework in order to extract concepts from image captions. Next, an ontology-based framework is deployed in order to resolve natural language ambiguities. The novelty of the proposed framework is that the combination of LSI with the Ontology framework enables the combined framework to tolerate ambiguities and variations in the Ontology. A key feature is that the system can find indirectly relevant concepts in image captions and thus leverage these to represent the semantics of images at a higher level. Experimental results show that the use of LSI based NLP combined with an ontological framework significantly enhances image retrieval.

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Section: Proposed Frameworkmentioning

confidence: 99%

“…There are many specific content domains, of interest to different communities of users. One such content domain that has strong universal appeal is the sports domain [1]. Multimedia content can benefit from a multimedia specific retrieval system, rather than using a traditional textbased retrieval system.…”

Section: Introductionmentioning

confidence: 99%

Semantic Restructuring of Natural Language Image Captions to Enhance Image Retrieval

Kesorn¹,

Poslad²

2009

JMM

Self Cite

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“…[14] aims at enabling real-time interaction between audiences and the video director, so that the video director can schedule future broadcasts based on viewers' feedback about which parallel sports event they enjoy more. [10] endeavors to facilitate personalized video delivery by enabling a viewer to customize the live sports video according to his own interest. Based on multi-camera angle selection, athletes/objects matching the personal preferences can be automatically tracked.…”

Section: Introductionmentioning

confidence: 99%

My Second Bike: A TV-Enabled Social and Interactive Riding Experience

Chung

Colaço

et al. 2010

2010 7th IEEE Consumer Communications and Networking Conference

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In this paper, we propose a novel concept for a social TV application targeting the demographic of viewers enjoying live sports events, such as road bicycle racing. We intend to enhance the viewing experiences of spectators with sensor-fitted bikes tied to an interactive biking environment on television. The system enables a new form of personalized, physical, and virtualreality interaction between viewers and a TV program, as well as interactions within or between communities of friends. We also describe a prototype we have implemented to demonstrate the feasibility of our idea. The prototype, My Second Bike, uses a 3D mirrored world environment (Google Earth) to visually represent participating spectators, competing athletes and outdoor bikers. We contend that the system has the potential to attract and support a large user base on account of its scalability, ease of deployment and ability to promote audience participation in live sports events on TV.

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Personalising live zooming using the ePlayer

Wang

2013

Multimedia Systems

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Directing your own live and interactive sports channel

Cited by 5 publications

References 10 publications

Semantic Restructuring of Natural Language Image Captions to Enhance Image Retrieval

Semantic Restructuring of Natural Language Image Captions to Enhance Image Retrieval

My Second Bike: A TV-Enabled Social and Interactive Riding Experience

Personalising live zooming using the ePlayer

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