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Ego-Action Analysis for First-Person Sports Videos
April-June 2012 (vol. 11 no. 2)
pp. 92-95

A new algorithm enables a fully automatic real-time video segmentation solution for dynamic first-person sports videos. The proposed approach leverages the latest in robust vision-based ego-motion estimation and unsupervised learning using nonparametric Bayesian modeling.

1. K.M. Kitani et al., "Fast Unsupervised Ego-Action Learning for First-Person Sports Videos," Proc. IEEE Conf. Computer Vision and Pattern Recognition, IEEE Press, 2011, pp. 3241–3248.

Index Terms:
wearable computing, pervasive computing, first-person point-of-view video, sports video analysis, ego-action, ego-motion
Citation:
Kris Kitani, "Ego-Action Analysis for First-Person Sports Videos," IEEE Pervasive Computing, vol. 11, no. 2, pp. 92-95, April-June 2012, doi:10.1109/MPRV.2012.28
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