Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
To search or to label?: predicting the performance of search-based automatic image classifiers
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Scalable search-based image annotation of personal images
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Practical elimination of near-duplicates from web video search
Proceedings of the 15th international conference on Multimedia
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Learning tag relevance by neighbor voting for social image retrieval
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Proceedings of the 18th international conference on World wide web
Proceedings of the 18th international conference on World wide web
Automatic video tagging using content redundancy
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
WSMC '09 Proceedings of the 1st workshop on Web-scale multimedia corpus
Scalable detection of partial near-duplicate videos by visual-temporal consistency
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Towards google challenge: combining contextual and social information for web video categorization
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Real-time near-duplicate elimination for web video search with content and context
IEEE Transactions on Multimedia - Special issue on integration of context and content
Enrichment and Ranking of the YouTube Tag Space and Integration with the Linked Data Cloud
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Learning social tag relevance by neighbor voting
IEEE Transactions on Multimedia
Unsupervised multi-feature tag relevance learning for social image retrieval
Proceedings of the ACM International Conference on Image and Video Retrieval
Automatic tag expansion using visual similarity for photo sharing websites
Multimedia Tools and Applications
On the Annotation of Web Videos by Efficient Near-Duplicate Search
IEEE Transactions on Multimedia
Enriching and localizing semantic tags in internet videos
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Tag suggestion and localization for web videos by bipartite graph matching
WSM '11 Proceedings of the 3rd ACM SIGMM international workshop on Social media
SynTag: a web-based platform for labeling real-time video
Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work
A social network for video annotation and discovery based on semantic profiling
Proceedings of the 21st international conference companion on World Wide Web
Assistive tagging: A survey of multimedia tagging with human-computer joint exploration
ACM Computing Surveys (CSUR)
Automatic extraction of relevant video shots of specific actions exploiting Web data
Computer Vision and Image Understanding
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Nowadays, almost any web site that provides means for sharing user-generated multimedia content, like Flickr, Facebook, YouTube and Vimeo, has tagging functionalities to let users annotate the material that they want to share. The tags are then used to retrieve the uploaded content, and to ease browsing and exploration of these collections, e.g. using tag clouds. However, while tagging a single image is straightforward, and sites like Flickr and Facebook allow also to tag easily portions of the uploaded photos, tagging a video sequence is more cumbersome, so that users just tend to tag the overall content of a video. Moreover, the tagging process is completely manual, and often users tend to spend as few time as possible to annotate the material, resulting in a sparse annotation of the visual content. A semi-automatic process, that helps the users to tag a video sequence would improve the quality of annotations and thus the overall user experience. While research on image tagging has received a considerable attention in the latest years, there are still very few works that address the problem of automatically assigning tags to videos, locating them temporally within the video sequence. In this paper we present a system for video tag suggestion and temporal localization based on collective knowledge and visual similarity of frames. The algorithm suggests new tags that can be associated to a given keyframe exploiting the tags associated to videos and images uploaded to social sites like YouTube and Flickr and visual features.