Using LSTM for Automatic Classification of Human Motion Capture Data

Rogério E. da Silva, Jan Ondřej, Aljosa Smolic
2019 Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications  
Creative studios tend to produce an overwhelming amount of content everyday and being able to manage these data and reuse it in new productions represent a way for reducing costs and increasing productivity and profit. This work is part of a project aiming to develop reusable assets in creative productions. This paper describes our first attempt using deep learning to classify human motion from motion capture files. It relies on a long short-term memory network (LSTM) trained to recognize
more » ... to recognize action on a simplified ontology of basic actions like walking, running or jumping. Our solution was able of recognizing several actions with an accuracy over 95% in the best cases.
doi:10.5220/0007349902360243 dblp:conf/grapp/SilvaOS19 fatcat:dg367kg7gzdhtbyldwp2ldhu3y