A semi-automatic approach to home video editing
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Affective content detection using HMMs
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Video shot segmentation using singular value decomposition
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
An improved valence-arousal emotion space for video affective content representation and recognition
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Advanced Data Mining Techniques
Advanced Data Mining Techniques
Utilizing affective analysis for efficient movie browsing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Automatic creation of photo books from stories in social media
Proceedings of second ACM SIGMM workshop on Social media
Generating adaptive multimedia presentations based on a semiotic framework
AI'05 Proceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence
Affective video content representation and modeling
IEEE Transactions on Multimedia
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In recent times, the proliferation of multimedia devices and reduced costs of data storage have enabled people to easily record and collect a large number of home videos; furthermore, this collection is growing with time. With the popularity of participatory media such as YouTube and facebook, problems are encountered when people intend to share their home videos with others. The first problem is that different people might be interested in different video content. Given the numbers of home videos, it is a time-consuming and hard task to manually select proper content for people with different interests. Secondly, as short videos are becoming more and more popular in media sharing applications, people need to manually cut and edit home videos which is again a tedious task. In this paper, we propose a method that employs affective analysis to automatically create video presentations from home videos. Our novel method adaptively creates presentations based on three properties: emotional tone, local main character and global main character. A novel sparsity-based affective labeling method is proposed to identify the emotional content of the videos. The local and global main characters are determined by applying face recognition in each shot. To demonstrate the proposed method, three kinds of presentations are created for family, acquaintance and outsider. Experimental results show that our method is very effective in video sharing and the users are satisfied with the videos generated by our method.