Insaf Ajili and Malik Mallem and Jean-Yves Didier
Relevant LMA Features for Human Motion Recognition
792 - 796
2018
12
9
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/10009574
https://publications.waset.org/vol/141
World Academy of Science, Engineering and Technology
Motion recognition from videos is actually a very
complex task due to the high variability of motions. This paper
describes the challenges of human motion recognition, especially
motion representation step with relevant features. Our descriptor
vector is inspired from Laban Movement Analysis method. We
propose discriminative features using the Random Forest algorithm
in order to remove redundant features and make learning algorithms
operate faster and more effectively. We validate our method on
MSRC12 and UTKinect datasets.
Open Science Index 141, 2018