A PREDICTION METHOD OF GESTURE TRAJECTORY BASED ON LEAST SQUARES FITTING MODEL

A PREDICTION METHOD OF GESTURE TRAJECTORY BASED ON LEAST SQUARES FITTING MODEL

Cai Mengmeng^1,2 Feng Zhiquan^1,2 and Luan Min^1,2

¹School of Information Science and Engineering,

University of Jinan, Jinan, China 250022

²Shandong Provincial Key Laboratory of Network-based Intelligent Computing,

Jinan, China, 250022, P.R.

ABSTRACT

Implicit interaction based on context information is widely used and studied in the virtual scene. In context based human computer interaction, the meaning of action A is well defined. For instance, the right wave is defined turning paper or PPT in context B, And it mean volume up in context C. However, we cannot use the context information when we select the object to be manipulated. In view of this situation, this paper proposes using the least squares fitting curve beam to predict the user's trajectory, so as to determine what object the user’s wants to operate. At the same time, the fitting effects of the three curves were compared, and the curve which is more accord with the hand movement trajectory is obtained. In addition, using the bounding box size control the Z variable to move in an appropriate location. Experimental results show that the proposed in this paper based on bounding box size to control the Z variables get a good effect; by fitting the trajectory of a human hand, to predict the object that the subjects would like to operate. The correct rate is 91%.

KEYWORDS

Least-squares method; dynamic gesture recognition; implicit interaction; edge point sequential extraction; context information 

Original Source URL :

http://aircconline.com/vlsics/V8N1/8117vlsi01.pdf

For More Details :

http://airccse.org/journal/vlsi/vol8.html