Time as essence for photo browsing through personal digital libraries
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
Link analysis ranking: algorithms, theory, and experiments
ACM Transactions on Internet Technology (TOIT)
Leveraging context to resolve identity in photo albums
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Why we tag: motivations for annotation in mobile and online media
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Toward content-aware multimodal tagging of personal photo collections
Proceedings of the 9th international conference on Multimodal interfaces
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Efficient pattern matching over event streams
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Annotating photo collections by label propagation according to multiple similarity cues
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Methods for extracting place semantics from Flickr tags
ACM Transactions on the Web (TWEB)
Context-aware person identification in personal photo collections
IEEE Transactions on Multimedia - Special issue on integration of context and content
Beyond pixels: Exploiting camera metadata for photo classification
Pattern Recognition
Content without context is meaningless
Proceedings of the international conference on Multimedia
Automatic image semantic interpretation using social action and tagging data
Multimedia Tools and Applications
Describable Visual Attributes for Face Verification and Image Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of Face Recognition
Ontological distance measures for information visualisation on conceptual maps
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part II
Methods for extracting place semantics from Flickr tags
ACM Transactions on the Web (TWEB)
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An image recognition problem is typically formulated as tagging a given set of images with labels from a predefined set. Context-aware approaches in problems like face recognition have utilized information about a user and the people she knows through different social networks. Traditionally, this context is statically linked to all of the available data. In this work, we propose a technique to dynamically discover which subset of all the available data is relevant context for the given recognition problem. In this dissertation, we propose the CueNet framework, to discover candidate labels for the person identification problem in personal photos. We describe our context model, and how it allows heterogeneous data sources to contribute useful context for the identification problem. We design algorithms to extract contextual information from these sources to discover a subset of candidates who could potentially appear in personal photos. Our early experiments show that CueNet is capable of removing upto 99% of irrelevant candidates, and was able to correctly tag 80% of frontal faces.