TY - JOUR
T1 - Automatic image semantic interpretation using social action and tagging data
AU - Sawant, Neela
AU - Li, Jia
AU - Wang, James Z.
N1 - Funding Information:
The material was based upon work supported in part by the National Science Foundation under Grant Nos. IIS-0949891 and IIS-0347148, and by The Pennsylvania State University.
PY - 2011/1
Y1 - 2011/1
N2 - The plethora of social actions and annotations (tags, comments, ratings) from online media sharing Websites and collaborative games have induced a paradigm shift in the research on image semantic interpretation. Social inputs with their added context represent a strong substitute for expert annotations. Novel algorithms have been designed to fuse visual features with noisy social labels and behavioral signals. In this survey, we review nearly 200 representative papers to identify the current trends, challenges as well as opportunities presented by social inputs for research on image semantics. Our study builds on an interdisciplinary confluence of insights from image processing, data mining, human computer interaction, and sociology to describe the folksonomic features of users, annotations and images. Applications are categorized into four types: concept semantics, person identification, location semantics and event semantics. The survey concludes with a summary of principle research directions for the present and the future.
AB - The plethora of social actions and annotations (tags, comments, ratings) from online media sharing Websites and collaborative games have induced a paradigm shift in the research on image semantic interpretation. Social inputs with their added context represent a strong substitute for expert annotations. Novel algorithms have been designed to fuse visual features with noisy social labels and behavioral signals. In this survey, we review nearly 200 representative papers to identify the current trends, challenges as well as opportunities presented by social inputs for research on image semantics. Our study builds on an interdisciplinary confluence of insights from image processing, data mining, human computer interaction, and sociology to describe the folksonomic features of users, annotations and images. Applications are categorized into four types: concept semantics, person identification, location semantics and event semantics. The survey concludes with a summary of principle research directions for the present and the future.
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U2 - 10.1007/s11042-010-0650-8
DO - 10.1007/s11042-010-0650-8
M3 - Article
AN - SCOPUS:78651384365
SN - 1380-7501
VL - 51
SP - 213
EP - 246
JO - Multimedia Tools and Applications
JF - Multimedia Tools and Applications
IS - 1
ER -