@inproceedings {2014,
	title = {From Continuous Affective Space to Continuous Expression Space: Non-Verbal Behaviour Recognition and Generation},
	booktitle = {Proc. 4th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL-Epirob 2014)},
	year = {2014},
	note = {<a href="https://ieeexplore.ieee.org/document/6982957">Download</a>},
	month = {10/2014},
	pages = {75{\textendash}80},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Genoa, Italy},
	abstract = {In this research, a recurrent neural network with parametric bias (RNNPB) was adopted to construct a continuous expression space from emotion caused human behaviours. It made use of the short-term memory ability of the recurrent weights to store spatio-temporal sequences features, while the attached parametric bias units were trained in a self-organizing way and represented as a low-dimensional expression space to capture these non-linear features of the sequences. Three demonstrations were given: training and recognition performances were examined in computer simulations, while the network generated both trained and novel movements were shown in a three-dimensional avatar demonstrations.},
	doi = {10.1109/DEVLRN.2014.6982957},
	url = {http://ieeexplore.ieee.org/document/6982957/},
	author = {Junpei Zhong and Lola Ca{\~n}amero}
}
