@InProceedings{paggio-navarretta-jongejan:2017:VL17,
  author    = {Paggio, Patrizia  and  Navarretta, Costanza  and  Jongejan, Bart},
  title     = {Automatic identification of head movements in video-recorded conversations: can words help?},
  booktitle = {Proceedings of the Sixth Workshop on Vision and Language},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {40--42},
  abstract  = {We present an approach where an SVM classifier learns to classify head
	movements based on measurements of velocity, acceleration, and the third
	derivative of position with respect to time, jerk. Consequently,
	annotations of head movements are added to new video data. The results of the
	automatic annotation are evaluated against manual annotations in the same data
	and show an accuracy of 68% with respect to these. The results also show that
	using jerk improves accuracy. We then conduct an investigation of the
	overlap between temporal sequences classified as either movement or
	non-movement and the speech
	stream of the person performing the gesture. The statistics derived from this
	analysis show that using word features may help increase the accuracy of the
	model.},
  url       = {http://www.aclweb.org/anthology/W17-2006}
}