Research on computer vision enhancement in intelligent robot based on machine learning and deep learning

被引:0
作者
Yuhan Ding
Lisha Hua
Shunlei Li
机构
[1] Facoltà Di Ingegneria Dell’Università Di Bologna,Mechanical Engineering
[2] City University of Hongkong,State Key Laboratory of Tribology
[3] Tsinghua University,undefined
来源
Neural Computing and Applications | 2022年 / 34卷
关键词
Machine learning; Deep learning; Robotics; Machine vision;
D O I
暂无
中图分类号
学科分类号
摘要
The stable operation of intelligent robots requires the effective support of machine vision technology. In order to improve the effect of robot machine vision recognition, based on deep learning, this paper, under the guidance of machine learning ideas, proposes a target detection framework that combines target recognition and target tracking based on the efficiency advantages of the KCF visual tracking algorithm. Moreover, this paper designs a vision system based on a high-resolution color camera and TOF depth camera. In addition, by modeling the coordinate conversion relationship of the same object in the camera coordinate system of two cameras, the projection relationship of the depth map collected by the TOF camera to the pixel coordinate system of the high-resolution color camera is determined. In addition, this paper designs experiments to verify the performance of the model. The research results show that the method proposed in this paper has a certain effect.
引用
收藏
页码:2623 / 2635
页数:12
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  • [21] Yang Y(2017)Review of underwater machine vision technology and its applications[J] Mar Technol Soc J 51 75-97
  • [22] Miao C(2016)Electrochemical fabrication of silver tips for tip-enhanced Raman spectroscopy assisted by a machine vision system[J] J Raman Spectrosc 47 808-812
  • [23] Li X(2016)Battery-free connected machine vision with wispcam[J] GetMobile Mobile Comput Commun 20 10-13
  • [24] Sun TH(2019)Design, development, and evaluation of a target oriented weed control system using machine vision[J] Turkish J Agric For 43 164-173
  • [25] Tien FC(2018)Digital foveation: An energy-aware machine vision framework[J] IEEE Trans Comput Aided Des Integr Circuits Syst 37 2371-2380
  • [26] Tien FC(2016)Contusion and recovery of individual cognitive based on catastrophe theory: a computational model[J] Neurocomputing 220 210-220
  • [27] Silwal A(undefined)undefined undefined undefined undefined-undefined
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