Creating map-based storyboards for browsing tour videos

Watching a long unedited video is usually a boring experience. In this paper we examine a particular subset of videos, tour videos, in which the video is captured by walking about with a running camera with the goal of conveying the essence of some place. We present a system that makes the process of sharing and watching a long tour video easier, less boring, and more informative. To achieve this, we augment the tour video with a map-based storyboard, where the tour path is reconstructed, and coherent shots at different locations are directly visualized on the map. This allows the viewer to navigate the video in the joint location-time space. To create such a storyboard we employ an automatic pre-processing component to parse the video into coherent shots, and an authoring tool to enable the user to tie the shots with landmarks on the map. The browser-based viewing tool allows users to navigate the video in a variety of creative modes with a rich set of controls, giving each viewer a unique, personal viewing experience. Informal evaluation shows that our approach works well for tour videos compared with conventional media players.

[1]  Andrew Lippman,et al.  Movie-maps: An application of the optical videodisc to computer graphics , 1980, SIGGRAPH '80.

[2]  Yoshinobu Tonomura,et al.  VideoMAP and VideoSpaceIcon: tools for anatomizing video content , 1993, INTERCHI.

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

[4]  Gary Marchionini,et al.  Key frame preview techniques for video browsing , 1998, DL '98.

[5]  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.

[6]  Rainer Lienhart,et al.  Abstracting home video automatically , 1999, MULTIMEDIA '99.

[7]  Jeho Nam,et al.  Video abstract of video , 1999, 1999 IEEE Third Workshop on Multimedia Signal Processing (Cat. No.99TH8451).

[8]  Shingo Uchihashi,et al.  A semi-automatic approach to home video editing , 2000, UIST '00.

[9]  Jonathan Foote,et al.  Scene boundary detection via video self-similarity analysis , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[10]  Ying Li,et al.  An Overview of Video Abstraction Techniques , 2001 .

[11]  Jiri Matas,et al.  Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..

[12]  Kentaro Toyama,et al.  Geographic location tags on digital images , 2003, ACM Multimedia.

[13]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[14]  Mor Naaman,et al.  Automatic organization for digital photographs with geographic coordinates , 2004, Proceedings of the 2004 Joint ACM/IEEE Conference on Digital Libraries, 2004..

[15]  Cordelia Schmid,et al.  Scale & Affine Invariant Interest Point Detectors , 2004, International Journal of Computer Vision.

[16]  H. Garcia-Molina,et al.  Automatic organization for digital photographs with geographic coordinates , 2004, Proceedings of the 2004 Joint ACM/IEEE Conference on Digital Libraries, 2004..

[17]  Katsumi Tanaka,et al.  3D viewpoint-based photo search and information browsing , 2005, SIGIR '05.

[18]  Steven M. Seitz,et al.  Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..

[19]  David Salesin,et al.  A framework for video annotation, visualization, and interaction , 2007 .

[20]  Ba Tu Truong,et al.  Video abstraction: A systematic review and classification , 2007, TOMCCAP.