VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Using event segmentation to improve indexing of consumer photographs
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Time as essence for photo browsing through personal digital libraries
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
Ontology-Based Photo Annotation
IEEE Intelligent Systems
How do people manage their digital photographs?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries
MPEG-7 Based Dozen Dimensional Digital Content Architecture for Semantic Image Retrieval Services
EEE '04 Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04)
Semi-automatic, data-driven construction of multimedia ontologies
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Enhancing the semantic interoperability of multimedia through a core ontology
IEEE Transactions on Circuits and Systems for Video Technology
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The current trend of image retrieval is to incorporate the image visual features used in Content Based Image Retrieval (CBIR) and semantics annotations used in Metadata Based Image Retrieval to enhance retrieval performance. Because of the pervasive of consumer imaging devices, building personal digital photograph libraries became an increasingly interested domain. Personal digital photograph collections have specific characteristics compare to general purpose image databases. Hence, annotation architecture specially designed for that plays an important role in building an interoperatable data repository for future indexing, browsing and retrieving purposes. We propose a MPEG- 7 based multimedia content description architecture, Dozen Dimensional Digital Content (DDDC), which annotates multimedia data with twelve main attributes regarding its semantic representation. In addition, we also proposed a machine-understandable "Spatial and Temporal Based Ontology" representation for the above DDDC semantics description to enable semi-automatic annotation process.