Computational Media Aesthetics: Finding Meaning Beautiful
IEEE MultiMedia
Creating music videos using automatic media analysis
Proceedings of the tenth ACM international conference on Multimedia
Pivot Vector Space Approach for Audio-Video Mixing
IEEE MultiMedia
Robust Real-Time Face Detection
International Journal of Computer Vision
Multimodal approach to measuring excitement in video
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
A generic framework of user attention model and its application in video summarization
IEEE Transactions on Multimedia
Shot-boundary detection: unraveled and resolved?
IEEE Transactions on Circuits and Systems for Video Technology
Optimization-based automated home video editing system
IEEE Transactions on Circuits and Systems for Video Technology
A User Experience Model for Home Video Summarization
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Using cross-media correlation for scene detection in travel videos
Proceedings of the ACM International Conference on Image and Video Retrieval
The art of video MashUp: supporting creative users with an innovative and smart application
Multimedia Tools and Applications
Travel photo and video summarization with cross-media correlation and mutual influence
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
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In this paper, we propose an automatic home video skimming system based on media aesthetics. Unlike other similar works, the proposed system considers video editing theory and realizes the idea of computational media aesthetics. Given a home video and a incidental background music, this system generates a music video (MV) style skimming video automatically, with consideration of video quality, music tempo, and the editing theory. The background music is analyzed so that visual rhythm caused by shot changes in the skimming video are synchronous with the music tempo. Our work focuses on the rhythm over aesthetic features, which is more recognizable and more suitable to describe the relationship between video and audio. Experiments show that the generated skimming video is effective in representing the original input video, and the audio-video conformity is satisfactory.