2A2-E30 Target tracking control using a high-speed active vision with zoom and focus mechanism

2010 ◽  
Vol 2010 (0) ◽  
pp. _2A2-E30_1-_2A2-E30_3
Author(s):  
TAEYEON KIM ◽  
Akio NAMIKI
Keyword(s):  
Target Tracking ◽  
Tracking Control ◽  
High Speed ◽  
Active Vision

Target Tracking of Moving and Rotating Object by High-Speed Monocular Active Vision

2020 ◽  
Vol 20 (12) ◽  
pp. 6727-6744
Author(s):  
Yang Liu ◽  
Pansiyu Sun ◽  
Akio Namiki
Keyword(s):  
Target Tracking ◽  
High Speed ◽  
Active Vision

2A1-T10 Target Tracking Using High-speed Active-vision Mounted on UAV

2015 ◽  
Vol 2015 (0) ◽  
pp. _2A1-T10_1-_2A1-T10_2
Author(s):  
Pan YANG ◽  
Qingyi GU ◽  
Tadayoshi AOYAMA ◽  
Takeshi TAKAKI ◽  
Idaku ISHII
Keyword(s):  
Target Tracking ◽  
High Speed ◽  
Active Vision

Study on Driver and Vehicle System With Lane-Tracking Control System Using Steering Torque Input

2001 ◽  
Author(s):  
Masao Nagai ◽  
Hidehisa Yoshida ◽  
Kiyotaka Shitamitsu ◽  
Hiroshi Mouri
Keyword(s):  
Tracking Control ◽  
High Speed ◽  
Driving Simulator ◽  
Tracking System ◽  
Torque Control ◽  
Steering Wheel ◽  
Control Input ◽  
Steering Angle ◽  
Lane Tracking ◽  
Steering Torque

Abstract Although the vast majority of lane-tracking control methods rely on the steering wheel angle as the control input, a few studies have treated methods using the steering torque as the input. When operating vehicles especially at high speed, drivers typically do not grip the steering wheel tightly to prevent the angle of the steering wheel from veering off course. This study proposes a new steering assist system for a driver not with the steering angle but the steering torque as the input and clarifies the characteristics and relative advantages of the two approaches. Then using a newly developed driving simulator, characteristics of human drivers and the lane-tracking system based on the steering torque control are investigated.

scholarly journals Achievement Method of High-Speed Response of Error Prediction Tracking Control for Optical Disk System

2007 ◽  
Vol 127 (9) ◽  
pp. 942-949 ◽  
Author(s):  
Toru Hayano ◽  
Isao Shibutani ◽  
Kiyoshi Ohishi ◽  
Toshimasa Miyazaki ◽  
Daiichi Koide ◽  
...  
Keyword(s):  
Tracking Control ◽  
High Speed ◽  
Optical Disk ◽  
Error Prediction ◽  
Disk System ◽  
Speed Response

Tracking algorithm of snowboard target in intelligent system

2020 ◽  
pp. 1-9
Author(s):  
Zhipeng Li ◽  
Xiaolan Li ◽  
Ming Shi ◽  
Wenli Song ◽  
Guowei Zhao ◽  
...  
Keyword(s):  
Target Tracking ◽  
High Speed ◽  
Intelligent System ◽  
Mean Shift ◽  
Target Position ◽  
Tracking Algorithm ◽  
Tracking Accuracy ◽  
Mean Shift Algorithm ◽  
Target Track ◽  
The Mean

Snowboarding is a kind of sport that takes snowboarding as a tool, swivels and glides rapidly on the specified slope line, and completes all kinds of difficult actions in the air. Because the sport is in the state of high-speed movement, it is difficult to direct guidance during the sport, which is not conducive to athletes to find problems and correct them, so it is necessary to track the target track of snowboarding. The target tracking algorithm is the main solution to this task, but there are many problems in the existing target tracking algorithm that have not been solved, especially the target tracking accuracy in complex scenes is insufficient. Therefore, based on the advantages of the mean shift algorithm and Kalman algorithm, this paper proposes a better tracking algorithm for snowboard moving targets. In the method designed in this paper, in order to solve the problem, a multi-algorithm fusion target tracking algorithm is proposed. Firstly, the SIFT feature algorithm is used for rough matching to determine the fuzzy position of the target. Then, the good performance of the mean shift algorithm is used to further match the target position and determine the exact position of the target. Finally, the Kalman filtering algorithm is used to further improve the target tracking algorithm to solve the template trajectory prediction under occlusion and achieve the target trajectory tracking algorithm design of snowboarding.

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