Girmaw Abebe Tadesse, Oliver Bent, et al.
IEEE SPM
This paper presents a framework for providing video digests that are personalized by profiles of individual users. Video contents have meta-data described manually from a set of predefined keywords that have temporal duration. Content profiles are prepared by a provider, which are vectors of importance value of keywords, and the only one should be selected by a user. In addition, a user profile is collected by the user, which has the same components. The importance scores of an image sequence along the time axis can be calculated from the combination of these profiles. Finally, the video clips can be collected as the video digest from the whole contents, which have higher importance scores than a threshold transformed from the length of the user requirement.
Girmaw Abebe Tadesse, Oliver Bent, et al.
IEEE SPM
Xiaohui Shen, Gang Hua, et al.
FG 2011
R.A. Gopinath, Markus Lang, et al.
ICIP 1994
Silvio Savarese, Holly Rushmeier, et al.
Proceedings of the IEEE International Conference on Computer Vision