As the advancement of social platform, media capturing devices, and media processing tools, large volumes of user-generated content or professionally edited content are shared and disseminated on the Web. Internet users can browse, comment, edit, and sometimes creatively re-compose this content to generate new media, giving new insights or interesting applications. A fundamental question, therefore, arises - Why are we attracted to multimedia content and services? How can we make our multimedia content, services, and experiences more attractive? Massive multimedia data shared on social media platforms apparently raise multimedia research challenges and opportunities; however, few research efforts have been put on these interesting and challenging topics. This workshop is intended to provide a forum for researchers and engineers to present their latest innovations and share their experiences on all aspects of attractiveness computing in multimedia.
Creation: content synthesis and collaboration; creation of novel attractive content.
Editing: content authoring, composition, summarization, and presentation; multimodality integration.
Indexing and retrieval: novel features and structure to index multimedia by its attractiveness score; retrieval interface and model; socially-aware analysis.
Methodology: machine learning for attractiveness analysis; classification and pattern recognition; generic model and heuristics in analysis.
Interaction: interaction on various devices; user in the loop of computation; human factors in attractiveness.
Actuation: navigation; recommendation.
Evaluation: dataset development; evaluation of systems; design of user study; limitation of the state-of-the-art.
Novel applications: novel application scenarios; development of novel challenges and perspectives.
04月19日
2017
04月21日
2017
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