Rajiv Shah, Roger Zimmermann

Multimodal Analysis of User-Generated Multimedia Content (eBook, PDF)

• Format: PDF

Produktbeschreibung

Detailed summary of multimodal analysis of user-generated multimedia content literature

Proposed frameworks for several significant multimedia systems based on user-generated content

Leveraging multimodal information in solving several significant multimedia analytics problems

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 263
• Erscheinungstermin: 30. August 2017
• Englisch
• ISBN-13: 9783319618074
• Artikelnr.: 53058386

Autorenporträt

Rajiv Ratn Shah received his B.Sc. with honors in Mathematics from Banaras Hindu University, India in 2005. He received his M.Tech. in Computer Technology and Applications from Delhi Technological University, India in 2010. Prior joining Indraprastha Institute of Information Technology Delhi (IIIT Delhi), India as an assistant professor, Dr Shah has received his Ph.D. in Computer Science from the National University of Singapore, Singapore. Currently, he is also working as a research fellow in living analytics research centre (LARC) at the Singapore Management University, Singapore. His research interests include the multimodal analysis of user-generated multimedia content in the support of social media applications, multimodal event detection and recommendation, and multimedia analysis, search, and retrieval. Dr Shah is the recipient of several awards, including the runner-up in the Grand Challenge competition of ACM International Conference on Multimedia. He is involved in reviewingof many top-tier international conferences and journals. He has published several research work in top-tier conferences and journals such as Springer MultiMedia Modeling, ACM International Conference on Multimedia, IEEE International Symposium on Multimedia, and Elsevier Knowledge-Based Systems.

Inhaltsangabe

Introduction.- Literature Review.- Event Understanding.- Tag Recommendation and Ranking.- Soundtrack Recommendation for UGVs.- Lecture Video Segmentation.- Adaptive News Video Uploading.- Conclusions and future work.