Content-based video indexing for sports applications using integrated multi-modal approach

ABSTRACT

To sustain an ongoing rapid growth of video information, there is an emerging demand for a sophisticated content-based video indexing system. However, current video indexing solutions are still immature and lack of any standard. This doctoral consists of a research work based on an integrated multi-modal approach for sports video indexing and retrieval. By combining specific features extractable from multiple audio-visual modalities, generic structure and specific events can be detected and classified. During browsing and retrieval, users will benefit from the integration of high-level semantic and some descriptive mid-level features such as whistle and close-up view of player(s).

REFERENCES

• 1: Ekin, A. and Tekalp, M. Automatic Soccer Video Analysis and Summarization. IEEE Transaction on Image Processing, 12 (7). 796--807.
• 2: Surya Nepal , Uma Srinivasan , Graham Reynolds, Automatic detection of 'Goal' segments in basketball videos, Proceedings of the ninth ACM international conference on Multimedia, September 30-October 05, 2001, Ottawa, Canada [doi>10.1145/500141.500181]
• 3: Wu, C., Ma, Y.-F., Zhang, H.-J. and Zhong, Y.-Z., Events recognition by semantic inference for sports video. in Multimedia and Expo, 2002. Proceedings. 2002 IEEE International Conference on, (2002), 805--808.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Abstracting methods

General Terms:
Algorithms, Experimentation

Keywords:
multi-modal event detection, sports video indexing