Latent Spatio-temporal Models for Action Localization and Recognition in Nursing Home Surveillance Video
Yuke Zhu, Tian Lan, Yijian Yang, Stephen N. Robinovitch, Greg Mori · 2013
This paper presents an application of vision-based monitoring of long-term care facility residents. We de-velop an algorithm to detect events of interest, partic-ularly falls by elderly residents. The algorithm uses a max-margin latent variable approach with spatio-temporal locations of the person in the video as latent variables. The recently developed Action Bank descrip-tor is utilized as a rich feature representation for each frame. Empirical results demonstrate the effectiveness of this method. 1