Title
An Intention Understanding Algorithm Based on Multimodal Information Fusion
Abstract
This paper proposes an intention understanding algorithm (KDI) based on an elderly service robot, which combines Neural Network with a seminaive Bayesian classifier to infer user's intention. KDI algorithm uses CNN to analyze gesture and action information, and YOLOV3 is used for object detection to provide scene information. Then, we enter them into a seminaive Bayesian classifier and set key properties as super parent to enhance its contribution to an intent, realizing intention understanding based on prior knowledge. In addition, we introduce the actual distance between the users and objects and give each object a different purpose to implement intent understanding based on object-user distance. The two methods are combined to enhance the intention understanding. The main contributions of this paper are as follows: (1) an intention reasoning model (KDI) is proposed based on prior knowledge and distance, which combines Neural Network with seminaive Bayesian classifier. (2) A set of robot accompanying systems based on the robot is formed, which is applied in the elderly service scene.
Year
DOI
Venue
2021
10.1155/2021/8354015
SCIENTIFIC PROGRAMMING
DocType
Volume
ISSN
Journal
2021
1058-9244
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Shaosong Dou100.34
Zhiquan Feng23613.73
Jinglan Tian301.01
Xue Fan400.68
Ya Hou500.34
Xin Zhang600.34