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Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Sentic Album: Content-, Concept-, and Context-Based Online Personal Photo Management System
Authors: Cambria, Erik
Hussain, Amir
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Keywords: Human computer interaction
Cognitive and affective information processing
Image affect
Image classification
Image features
Emotional semantic image retrieval
Sentic computing
Issue Date: Dec-2012
Publisher: Springer
Citation: Cambria E & Hussain A (2012) Sentic Album: Content-, Concept-, and Context-Based Online Personal Photo Management System, Cognitive Computation, 4 (4), pp. 477-496.
Abstract: The 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).
Type: Journal Article
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Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Affiliation: National University of Singapore
Computing Science - CSM Dept

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