Video Skimming and Characterization through the Combination of Image and Language Understanding
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Mosaic based representations of video sequences and their applications
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Object Categorization by Learned Universal Visual Dictionary
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
ACM SIGGRAPH 2006 Papers
Making a Long Video Short: Dynamic Video Synopsis
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Negative Samples Analysis in Relevance Feedback
IEEE Transactions on Knowledge and Data Engineering
Knowledge and Information Systems
VideoSense: towards effective online video advertising
Proceedings of the 15th international conference on Multimedia
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental tensor analysis: Theory and applications
ACM Transactions on Knowledge Discovery from Data (TKDD)
Data driven search organization for continuous speech recognition
IEEE Transactions on Signal Processing
A generic framework of user attention model and its application in video summarization
IEEE Transactions on Multimedia
Video visualization for compact presentation and fast browsing of pictorial content
IEEE Transactions on Circuits and Systems for Video Technology
Modality Mixture Projections for Semantic Video Event Detection
IEEE Transactions on Circuits and Systems for Video Technology
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The world is covered with millions of cameras with each recording a huge amount of video. It is a time-consuming task to watch these videos, as most of them are of little interest due to the lack of activity. Video representation is thus an important technology to tackle with this issue. However, conventional video representation methods mainly focus on a single video, aiming at reducing the spatiotemporal redundancy as much as possible. In contrast, this paper describes a novel approach to present the dynamics of multiple videos simultaneously, aiming at a less intrusive viewing experience. Given a main video and multiple supplementary videos, the proposed approach automatically constructs a synthesized multi-video synopsis by integrating the supplementary videos into the most suitable spatiotemporal portions within this main video. The problem of finding suitable integration between the main video and supplementary videos is formulated as the maximum a posterior (MAP) problem, in which the desired properties related to a less intrusive viewing experience, i.e., informativeness, consistency, visual naturalness, and stability, are maximized. This problem is solved by using an efficient Viterbi beam search algorithm. Furthermore, an informative blending algorithm that naturalizes the connecting boundary between different videos is proposed. The proposed method has a wide variety of applications such as visual information representation, surveillance video browsing, video summarization, and video advertising. The effectiveness of multi-video synopsis is demonstrated in extensive experiments over different types of videos with different synopsis cases.