Optimizing Gesture Recognition: A comparison of hidden Markov models and linear gesture recognition
This thesis aims to compare a simple linear recognition algorithm to that of
the well proven and reliable Hidden Markov Model. It implements a gesture
recognition system able to recognize gestures using both algorithms and com-
pares their performance before and after applying optimization techniques to
improve their speed and accuracy.
The system used to retrieve the results is developed using Java and is
aimed towards wearable devices as an alternate interaction technique for de-
vices with limited processing power.
The final conclusion from this thesis is that even a very simple recognition
algorithm can perform nearly as well as more complex ones if the data-sets
are presented well to the system.
Place, publisher, year, edition, pages
Institutt for datateknikk og informasjonsvitenskap , 2013. , 78 p.
IdentifiersURN: urn:nbn:no:ntnu:diva-21795Local ID: ntnudaim:7591OAI: oai:DiVA.org:ntnu-21795DiVA: diva2:644192
Wang, Alf Inge, FørsteamanuensisMcCallum, Simon