Paper Info
Title
Study on Action Recognition Based on Kinect and Its Application in Rehabilitation Training
Abstract
We introducted some basic structures and functions of Kinect briefly, analyzed depth images by aquiring camera body movement of the Kinect body feeling device. Further, we aquired 20 group node data by combinning with the SDK, so we proposed algorithm of gesture recognition by extracting feature vector in this paper. Representation method of action has been proposed based on the human body structure information. That is, according to the key points structure human body characteristic vector, we choosed the feature vector of the combination of vector Angle and vector modulus ratio to create human body posture to describe vector, and represented the action by using gesture description vector sequence. DTW algorithm is mainly studied, on the basis of the traditional DTW algorithm, improved and optimized the DTW (dynamic time warping) algorithm in this paper. Order to improve and optimize the DTW algorithm, we builded the template library operation and finished using improved DTW algorithm for identification matching experiments. Experimental data show that the improved DTW algorithm for simple action recognition rate is higher, and recognition rate is low for more complex action. The action recognition which based on access application is significance and feasibility in rehabilitation training.
Year
DOI
Venue
2015
10.1109/BDCloud.2015.38
BDCloud
Keywords
Field
DocType
skeleton,image recognition,gesture recognition,data mining
Computer vision,Feature vector,Dynamic time warping,Pattern recognition,Computer science,Gesture,Action recognition,Gesture recognition,Feature extraction,Body posture,Artificial intelligence,Eigenvalues and eigenvectors
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
nianfeng li100.34
yinfei dai200.34
Rong-quan Wang300.68
yanhui shao400.34