Stefan Wilk
Wolfgang Effelsberg
ABSTRACT
To compose high-quality movies directors need life-long learning and talent. User-generated video defines a new era of video production in which non-professionals record videos and share them on platforms such as YouTube. As hiring professional directors results in high costs, our work focuses on replacing those directors by crowdsourcing. The proposed system allows users to record and stream live videos to servers on which workers create a video mashup. A smartphone application for recording live video has been designed that supports the composition in the crowd by a multi-modal analysis of the recording quality. The contributions of this work are: The proposed system demonstrates that composing a large number of video views can be achieved in near real-time. Second, the system achieves comparable video quality for user-generated video in comparison to manual composition. Third, it offers insights on how to design real-time capable crowdsourcing systems. Fourth, by leveraging multi-modal features that can already be evaluated during recording the number of streams considered for presentation can be reduced.
- S. A. Ay, R. Zimmermann, and S. H. Kim. Viewable scene modeling for geospatial video search. In Proceeding of the 16th ACM international conference on Multimedia - MM '08, pages 309--318, 2008. Google Scholar
Digital Library
- M. S. Bernstein, J. Brandt, R. C. Miller, and D. R. Karger. Crowds in two seconds: enabling realtime crowd-powered interfaces. In ACM Symposium on User Interface Software and Technology, pages 33--42, 2011. Google ScholarDigital Library
- F. Cricri, K. Dabov, I. D. D. Curcio, S. Mate, and M. Gabbouj. Multimodal extraction of events and of information about the recording activity in user generated videos. Multimedia Tools and Applications, 70(1):119--158, 2012. Google ScholarDigital Library
- F. Cricri, M. Roininen, J. Leppaenen, S. Mate, I. Curcio, S. Uhlmann, and M. Gabbouj. Sport type classification of mobile videos. IEEE Transactions on Multimedia, 16(4): 917--932, 2014. Google ScholarDigital Library
- A. Engström, M. Esbjörnsson, and O. Juhlin. Mobile Collaborative Live Video Mixing. In Int. Conference on Human Computer Interaction with Mobile Devices and Services, pages 157--166, 2008. Google ScholarDigital Library
- R. Graham. An efficient algorithm for determining the convex hull of a finite planar set. In Information Processing Letters, 1972.Google Scholar
- ITU. ITU-R Recommendation P. 910. Technical report, 2008.Google Scholar
- ITU. ITU-R Recommendation BT.500. Technical report, 2012.Google Scholar
- S. Kim, Y. Lu, and G. Constantinou. MediaQ: mobile multimedia management system. In 5th ACM Multimedia Systems Conference, pages 224--235, 2014. Google ScholarDigital Library
- W. S. Lasecki, K. I. Murray, S. White, R. C. Miller, and J. P. Bigham. Real-time crowd control of existing interfaces. In ACM Symposium on User Interface Software and Technology, pages 23--32. Google ScholarDigital Library
- M. A. Mughal and O. Juhlin. Context-dependent software solutions to handle video synchronization and delay in collaborative live mobile video production. Personal and Ubiquitous Computing, 18(3):709--721, 2013. Google ScholarDigital Library
- M. J. Murphy, C. D. Miller, W. S. Lasecki, and J. P. Bigham. Adaptive time windows for real-time crowd captioning. In Extended Abstracts on Human Factors in Computing Systems, pages 13--18, 2013. Google ScholarDigital Library
- M. K. Saini, R. Gadde, S. Yan, and W. T. Ooi. MoViMash: Online Mobile Video Mashup. In ACM Int. Conference on Multimedia, pages 139--148, 2012. Google ScholarDigital Library
- P. Shrestha, P. H. de With, H. Weda, M. Barbieri, and E. H. Aarts. Automatic mashup generation from multiple-camera concert recordings. In ACM Int. Conference on Multimedia, pages 541--550, 2010. Google ScholarDigital Library
- G. Wang, B. Seo, and R. Zimmermann. Automatic positioning data correction for sensor-annotated mobile videos. In ACM Int. Conference on Advances in Geographic Information Systems, pages 470--473, 2012. Google ScholarDigital Library
- S. Wilk and W. Effelsberg. The influence of camera shakes, harmful occlusions and camera misalignment on the perceived quality in user-generated video. In IEEE Int. Conference on Multimedia and Expo, pages 1--6, 2014.Google ScholarCross Ref
- T. Yan, V. Kumar, and D. Ganesan. Crowdsearch: exploiting crowds for accurate real-time image search on mobile phones. In ACM Int. Conference on Mobile Systems, Applications, and Services, pages 77--90, 2010. Google ScholarDigital Library
- K.-c. Yang, C. Guest, and P. Das. Perceptual Sharpness Metric (PSM) for Compressed Video. In IEEE Int. Conference on Multimedia and Expo, pages 777--780, 2006.Google Scholar
Index Terms
- Video composition by the crowd: a system to compose user-generated videos in near real-time
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