2014
DOI: 10.4028/www.scientific.net/amm.670-671.1326
|View full text |Cite
|
Sign up to set email alerts
|

Binocular Vision Sensor (Kinect)-Based Pedestrian Following Mobile Robot

Abstract: This paper present a pedestrian following mobile robot with binocular vision sensor. Because Kinect is one of the most inexpensive devices of depth-cameras, it is used in our application. Human skeleton is extracted by using Kinect, and the location of human is checked by projecting the three-dimensional (3D) pose of skeleton onto 2D screen. This 2D screen is separated into three parts, left, middle and right. Mobile robot rotates and translates according to the corresponding location of pedestrian. To make th… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2017
2017
2022
2022

Publication Types

Select...
2
1
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(2 citation statements)
references
References 3 publications
(3 reference statements)
0
2
0
Order By: Relevance
“…They are based on information about the shape or colour of objects. Commonly methods such as SURF, SIFT, HOG, Haar and LBP are applied in object recognition [6][7][8][9][10]. The recent development in machine learning and deep learning approach has a great impact on the accuracy of object detecting and tracking.…”
Section: Introductionmentioning
confidence: 99%
“…They are based on information about the shape or colour of objects. Commonly methods such as SURF, SIFT, HOG, Haar and LBP are applied in object recognition [6][7][8][9][10]. The recent development in machine learning and deep learning approach has a great impact on the accuracy of object detecting and tracking.…”
Section: Introductionmentioning
confidence: 99%
“…They are based on information about the shape or colour of objects. Commonly methods such as SURF, SIFT, HOG, Haar and LBP are applied in object recognition [6][7][8][9][10]. The recent development in machine learning and deep learning approach has a great impact on the accuracy of object detecting and tracking.…”
Section: Introductionmentioning
confidence: 99%