Recognizing Strokes in Tennis Videos Using Hidden Markov Models


Petkovic, M. and Jonker, W. and Zivkovic, Z. (2001) Recognizing Strokes in Tennis Videos Using Hidden Markov Models. In: IASTED International Conference on Visualization, Imaging and Image Processing, VIIP 2001, 3-5 Sep 2001, Marbella, Spain (pp. pp. 512-516).

[img] PDF
Restricted to UT campus only
: Request a copy
Abstract:This paper addresses content-based video retrieval
with an emphasis on recognizing events in tennis game
videos. In particular, we aim at recognizing different
classes of tennis strokes using automatic learning
capability of Hidden Markov Models. Driven by our
domain knowledge, a robust player segmentation
algorithm is developed for real video data. Further, we
introduce a number of novel features to be extracted for
our particular application. Different feature combinations
are investigated in order to find the optimal one. The
experimental results demonstrate that our method is close
to realizing statistics of tennis games automatically using
ordinary TV broadcast videos.
Item Type:Conference or Workshop Item
Additional information:Imported from EWI/DB PMS [db-utwente:inpr:0000003225]
Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:
Link to this item:
Export this item as:BibTeX
HTML Citation
Reference Manager


Repository Staff Only: item control page