2014
DOI: 10.1109/tmech.2012.2228010
|View full text |Cite
|
Sign up to set email alerts
|

Integrating the Microsoft Kinect With Simulink: Real-Time Object Tracking Example

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
10
0
4

Year Published

2015
2015
2021
2021

Publication Types

Select...
5
5

Relationship

0
10

Authors

Journals

citations
Cited by 37 publications
(14 citation statements)
references
References 29 publications
0
10
0
4
Order By: Relevance
“…For example, [10] has integrated the Kinect with Simulink to allow for real-time object tracking. Reference [11] shows that the hardware sensor is applicable to the medical field through its use in a virtual rehabilitation system to help stroke victims regain balance.…”
Section: Related Workmentioning
confidence: 99%
“…For example, [10] has integrated the Kinect with Simulink to allow for real-time object tracking. Reference [11] shows that the hardware sensor is applicable to the medical field through its use in a virtual rehabilitation system to help stroke victims regain balance.…”
Section: Related Workmentioning
confidence: 99%
“…With the recent emergence of the motion recognition sensor can be more free from the influence of the tracking light [12], [13]. Motion Sensor such as Microsoft's Kinect have the advantage that high recognition rate by tracking human joint information.…”
Section: Motion Recognition Technologymentioning
confidence: 99%
“…In an effort to build robots which can autonomously implement some tasks in ever-changing environments, it is critical for a robot to have effectiveness of visual detection system. As a kind of feasible sensor with advantages of low power consumption, strong adaptability and low cost [1], digital cameras have been widely applied in robotics to realize target detection and tracking. In a machine vision-based robot, the visual detection system plays a very important role in realizing diverse robotic functions, such as target detection and tracking [2], [3], autonomous navigation [4], [5], mutual positioning [6], path planning [7]- [9], visual servoing [10], robot-human interaction [11], etc.…”
Section: Introductionmentioning
confidence: 99%