Please use this identifier to cite or link to this item: https://doi.org/10.1007/s12559-012-9145-4
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dc.titleSentic Album: Content-, Concept-, and Context-Based Online Personal Photo Management System
dc.contributor.authorCambria, E.
dc.contributor.authorHussain, A.
dc.date.accessioned2014-12-12T07:13:28Z
dc.date.available2014-12-12T07:13:28Z
dc.date.issued2012-12
dc.identifier.citationCambria, E., Hussain, A. (2012-12). Sentic Album: Content-, Concept-, and Context-Based Online Personal Photo Management System. Cognitive Computation 4 (4) : 477-496. ScholarBank@NUS Repository. https://doi.org/10.1007/s12559-012-9145-4
dc.identifier.issn18669956
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/115281
dc.description.abstractThe world of online personal photo management has come a long way in the past few years, but today, there are still huge gaps in annotating, organizing, and retrieving online pictures in such a way that they can be easily queried and visualized. Existing content-based image retrieval systems apply statistics, pattern recognition, signal processing, and computer vision techniques but these are still too weak to 'bridge the semantic gap' between the low-level data representation and the high-level concepts the user associates with images. Image meta search engines, on the other hand, rely on tags associated with online pictures but results are often too inaccurate since they mainly depend on keyword-based rather than concept-based algorithms. Sentic Album is a novel content-, concept-, and context-based online personal photo management system that exploits both data and metadata of online personal pictures to intelligently annotate, organize, and retrieve them. Many salient features of pictures, in fact, are only noticeable in the viewer's mind, and the cognitive ability to grasp such features is a key aspect for accordingly analyzing and classifying personal photos. To this end, Sentic Album exploits not just colors and texture of online images (content), but also the cognitive and affective information associated with their metadata (concept), and their relative timestamp, geolocation, and user interaction metadata (context). © 2012 Springer Science+Business Media, LLC.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s12559-012-9145-4
dc.sourceScopus
dc.subjectCognitive and affective information processing
dc.subjectEmotional semantic image retrieval
dc.subjectHuman computer interaction
dc.subjectImage affect
dc.subjectImage classification
dc.subjectImage features
dc.subjectSentic computing
dc.typeArticle
dc.contributor.departmentTEMASEK LABORATORIES
dc.description.doi10.1007/s12559-012-9145-4
dc.description.sourcetitleCognitive Computation
dc.description.volume4
dc.description.issue4
dc.description.page477-496
dc.identifier.isiut000312126300008
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