Real-time rotation invariant action recognition using Microsoft Kinect
Sarath Sasidaran Raniapsara, Ferat Sahin · 2016
A Human Action recognition system is proposed using the Skeletal Tracking from Kinect. The angular information of the joints helps in handling scaling errors. Vectors are generated using the joint coordinates and the angles of each joint are used as features for key pose recognition. A rotational compensation is included in the feature to handle rotational errors. The key poses are recognized using Similarity Matching Technique, neural network and decision tree algorithms. The recognized key postures are fed into a decision forest to pick the action based on the trained sequence of key poses.