Video de-abstraction or how to save money on your wedding video

There exist an increasing body of work dealing with video still abstraction, the extraction of representative still images from a video sequence. This work focuses in the other direction: given a video abstract and raw unedited video data, we produce an edited video. We focus on the application of generating wedding videos. We use the existing wedding photo album as an abstract, and produce an edited wedding video from it. The photo album serves us in determining importance of raw shots, as well as style and order.

[1]  Walter Bender,et al.  Salient Stills: Process and Practice , 1996, IBM Syst. J..

[2]  Alan Hanjalic,et al.  An integrated scheme for automated video abstraction based on unsupervised cluster-validity analysis , 1999, IEEE Trans. Circuits Syst. Video Technol..

[3]  Michal Irani,et al.  Video indexing based on mosaic representations , 1998, Proc. IEEE.

[4]  Edward H. Adelson,et al.  Representing moving images with layers , 1994, IEEE Trans. Image Process..

[5]  Richard Szeliski,et al.  A layered video object coding system using sprite and affine motion model , 1997, IEEE Trans. Circuits Syst. Video Technol..

[6]  Wolfgang Effelsberg,et al.  Abstracting Digital Movies Automatically , 1996, J. Vis. Commun. Image Represent..

[7]  Takeo Kanade,et al.  Video skimming and characterization through the combination of image and language understanding , 1998, Proceedings 1998 IEEE International Workshop on Content-Based Access of Image and Video Database.

[8]  John R. Kender,et al.  A unified memory based approach to cut, dissolve, key frame and scene analysis , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[9]  John R. Kender,et al.  Video Summaries through Mosaic-Based Shot and Scene Clustering , 2002, ECCV.

[10]  Alexander G. Hauptmann,et al.  Speech recognition in the Informedia Digital Video Library: uses and limitations , 1995, Proceedings of 7th IEEE International Conference on Tools with Artificial Intelligence.

[11]  Andrew Zisserman,et al.  Wide baseline stereo matching , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[12]  Luc Van Gool,et al.  Wide Baseline Stereo Matching based on Local, Affinely Invariant Regions , 2000, BMVC.