Intention-based home video browsing

ABSTRACT

This demonstration presents an efficient home video browsing system from a novel viewpoint -- capture intention. We extend our previous work to build up a comprehensive scheme to mine the capture intention, and based on this scheme, propose a novel home video browsing system. Such an intention based system assists both camcorder users and viewers to experience their personal home videos by providing two better manners of browsing -- by intention thumbnails and by intention curves. The user study indicates that our system offers users a more efficient way to search a given clip in a video than attention-based scheme.

REFERENCES

• 1: R. J. Gerrig and P. G. Zimbardo. Psychology and Life (16 Edition). Allyn & Bacon, 2001.
• 2: Yu-Fei Ma , Lie Lu , Hong-Jiang Zhang , Mingjing Li, A user attention model for video summarization, Proceedings of the tenth ACM international conference on Multimedia, December 01-06, 2002, Juan-les-Pins, France [doi>10.1145/641007.641116]
• 3: T. Mei, X.-S. Hua, H.-Q. Zhou, and S. Li. To mine the capture intention of camcorder users. In Proceedings of VCIP, 2005.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.1 Multimedia Information Systems
          Subjects: Video (e.g., tape, disk, DVI)

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.10 Vision and Scene Understanding
            Subjects: Video analysis

General Terms:
Algorithms, Experimentation, Human Factors

Keywords:
attention detection, capture intention, video content analysis