Sentic Album: Content-, Concept-, and Context-Based Online Personal Photo Management System

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 s...

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Veröffentlicht in:Cognitive computation Jg. 4; H. 4; S. 477 - 496
Hauptverfasser: Cambria, Erik, Hussain, Amir
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer-Verlag 01.12.2012
Springer Nature B.V
Schlagworte:
Algorithms
Annotations
Artificial Intelligence
Biomedical and Life Sciences
Biomedicine
Computation by Abstract Devices
Computational Biology/Bioinformatics
Computer vision
Context
Emotions
Image retrieval
Keywords
Memory
Metadata
Natural language
Neurosciences
Pattern recognition
Pictures
Retrieval
Search engines
Semantic web
Semantics
Sentiment analysis
Social networks
User generated content
Human computer interaction
Image features
Emotional semantic image retrieval
Image affect
Cognitive and affective information processing
Image classification
Sentic computing
ISSN:1866-9956, 1866-9964
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Zusammenfassung: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).
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ISSN:1866-9956
1866-9964
DOI:10.1007/s12559-012-9145-4