Abstract
Navigation in public spaces is an essential technique for pedestrian guidance and autonomous robot assistance. Navigation systems mainly consist of positioning systems, maps, route finding, and a user interface. Image acquisition or 3D sensing is also required to recognize the unknown environment around a pedestrian or robot. Therefore, we aim to develop a sense-and-avoid application for pedestrians and autonomous robots. We propose a real-time methodology to recognize the mobility area in an indoor environment using an active depth imager. In our experiments, we used a handheld time-of-flight (TOF) camera. We selected corridors, stairs, large rooms, and our laboratory in our campus as study areas. These areas consist of walls, glass walls, steps, and gaping holes. These objects were recognized with online processing, and notification for obstacle avoidance was issued after object recognition. Our experiments confirmed that our approach can process 3D measurements, classify objects, and notify for obstacle avoidance in real time.
| Original language | English |
|---|---|
| Title of host publication | 37th Asian Conference on Remote Sensing, ACRS 2016 |
| Publisher | Asian Association on Remote Sensing |
| Pages | 399-402 |
| Number of pages | 4 |
| Volume | 1 |
| ISBN (Electronic) | 9781510834613 |
| Publication status | Published - 2016 |
| Event | 37th Asian Conference on Remote Sensing, ACRS 2016 - Colombo, Sri Lanka Duration: 2016 Oct 17 → 2016 Oct 21 |
Other
| Other | 37th Asian Conference on Remote Sensing, ACRS 2016 |
|---|---|
| Country | Sri Lanka |
| City | Colombo |
| Period | 16/10/17 → 16/10/21 |
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Keywords
- Indoor navigation
- Object recognition
- Point cloud
- Time-of-flight camera
ASJC Scopus subject areas
- Computer Networks and Communications
Cite this
Real-time floor recognition in indoor environments using TOF Camera. / Nakagawa, Masafumi; Kobayashi, Tamaki.
37th Asian Conference on Remote Sensing, ACRS 2016. Vol. 1 Asian Association on Remote Sensing, 2016. p. 399-402.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Real-time floor recognition in indoor environments using TOF Camera
AU - Nakagawa, Masafumi
AU - Kobayashi, Tamaki
PY - 2016
Y1 - 2016
N2 - Navigation in public spaces is an essential technique for pedestrian guidance and autonomous robot assistance. Navigation systems mainly consist of positioning systems, maps, route finding, and a user interface. Image acquisition or 3D sensing is also required to recognize the unknown environment around a pedestrian or robot. Therefore, we aim to develop a sense-and-avoid application for pedestrians and autonomous robots. We propose a real-time methodology to recognize the mobility area in an indoor environment using an active depth imager. In our experiments, we used a handheld time-of-flight (TOF) camera. We selected corridors, stairs, large rooms, and our laboratory in our campus as study areas. These areas consist of walls, glass walls, steps, and gaping holes. These objects were recognized with online processing, and notification for obstacle avoidance was issued after object recognition. Our experiments confirmed that our approach can process 3D measurements, classify objects, and notify for obstacle avoidance in real time.
AB - Navigation in public spaces is an essential technique for pedestrian guidance and autonomous robot assistance. Navigation systems mainly consist of positioning systems, maps, route finding, and a user interface. Image acquisition or 3D sensing is also required to recognize the unknown environment around a pedestrian or robot. Therefore, we aim to develop a sense-and-avoid application for pedestrians and autonomous robots. We propose a real-time methodology to recognize the mobility area in an indoor environment using an active depth imager. In our experiments, we used a handheld time-of-flight (TOF) camera. We selected corridors, stairs, large rooms, and our laboratory in our campus as study areas. These areas consist of walls, glass walls, steps, and gaping holes. These objects were recognized with online processing, and notification for obstacle avoidance was issued after object recognition. Our experiments confirmed that our approach can process 3D measurements, classify objects, and notify for obstacle avoidance in real time.
KW - Indoor navigation
KW - Object recognition
KW - Point cloud
KW - Time-of-flight camera
UR - http://www.scopus.com/inward/record.url?scp=85018286956&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018286956&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85018286956
VL - 1
SP - 399
EP - 402
BT - 37th Asian Conference on Remote Sensing, ACRS 2016
PB - Asian Association on Remote Sensing
ER -