A semi-automatic approach to home video editing
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
A user attention model for video summarization
Proceedings of the tenth ACM international conference on Multimedia
Contrast-based image attention analysis by using fuzzy growing
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Optimization-based automated home video editing system
IEEE Transactions on Circuits and Systems for Video Technology
Personal media sharing and authoring on the web
Proceedings of the 13th annual ACM international conference on Multimedia
To learn representativeness of video frames
Proceedings of the 13th annual ACM international conference on Multimedia
Video summarization using personal photo libraries
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
User-adaptive home video summarization using personal photo libraries
Proceedings of the 6th ACM international conference on Image and video retrieval
Re-cinematography: Improving the camerawork of casual video
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
An efficient automatic video shot size annotation scheme
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Hi-index | 0.00 |
In this paper, we present a novel view to home video content analysis, which aims at tracking the capture intention of camcorder users. Based on the study of intention mechanism in psychology, a set of domain-specific capture intention concepts are defined. A comprehensive and extensible scheme consisting of video structuring, intention oriented feature analysis, as well as intention unit segmentation and classification is proposed to mine the users' capture intention. Experiments were carried on home video sequences of 90 hours in total, taken by 16 persons in recent 20 years. Both the user study and objective evaluations indicate that our proposed intention-based approach is an effective complement to existing home video content analysis schemes.