Abstract
Successful detection of people is a basic requirement for a robot to achieve symbiosis in people's daily life. Specifically, a mobile robot designed to follow people needs to keep track of people's position through time, for it defines the robot's position and trajectory. In this work we introduce the usage of reflection intensity data of Laser Range Finders (LRF) arranged in multiple layers for people detection. We use supervised learning to train strong classifiers including intensity-based features. Concretely, we propose a calibration method for laser intensity and introduce new intensity-based features for people detection which are combined with range-based features in a strong classifier using supervised learning. We provide experimental results to evaluate the effectiveness of these features. This work is an step towards of our main research project of developing a social autonomous mobile robot acting as member of a people group.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - IEEE International Workshop on Robot and Human Interactive Communication |
| Pages | 379-384 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2010 |
| Externally published | Yes |
| Event | 19th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2010 - Viareggio Duration: 2010 Sep 12 → 2010 Sep 15 |
Other
| Other | 19th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2010 |
|---|---|
| City | Viareggio |
| Period | 10/9/12 → 10/9/15 |
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ASJC Scopus subject areas
- Software
- Artificial Intelligence
- Human-Computer Interaction
Cite this
Laser reflection intensity and multi-layered laser range finders for people detection. / Carballo, Alexander; Ohya, Akihisa; Yuta, Shinichi.
Proceedings - IEEE International Workshop on Robot and Human Interactive Communication. 2010. p. 379-384 5598657.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Laser reflection intensity and multi-layered laser range finders for people detection
AU - Carballo, Alexander
AU - Ohya, Akihisa
AU - Yuta, Shinichi
PY - 2010
Y1 - 2010
N2 - Successful detection of people is a basic requirement for a robot to achieve symbiosis in people's daily life. Specifically, a mobile robot designed to follow people needs to keep track of people's position through time, for it defines the robot's position and trajectory. In this work we introduce the usage of reflection intensity data of Laser Range Finders (LRF) arranged in multiple layers for people detection. We use supervised learning to train strong classifiers including intensity-based features. Concretely, we propose a calibration method for laser intensity and introduce new intensity-based features for people detection which are combined with range-based features in a strong classifier using supervised learning. We provide experimental results to evaluate the effectiveness of these features. This work is an step towards of our main research project of developing a social autonomous mobile robot acting as member of a people group.
AB - Successful detection of people is a basic requirement for a robot to achieve symbiosis in people's daily life. Specifically, a mobile robot designed to follow people needs to keep track of people's position through time, for it defines the robot's position and trajectory. In this work we introduce the usage of reflection intensity data of Laser Range Finders (LRF) arranged in multiple layers for people detection. We use supervised learning to train strong classifiers including intensity-based features. Concretely, we propose a calibration method for laser intensity and introduce new intensity-based features for people detection which are combined with range-based features in a strong classifier using supervised learning. We provide experimental results to evaluate the effectiveness of these features. This work is an step towards of our main research project of developing a social autonomous mobile robot acting as member of a people group.
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UR - http://www.scopus.com/inward/citedby.url?scp=78649828262&partnerID=8YFLogxK
U2 - 10.1109/ROMAN.2010.5598657
DO - 10.1109/ROMAN.2010.5598657
M3 - Conference contribution
SN - 9781424479917
SP - 379
EP - 384
BT - Proceedings - IEEE International Workshop on Robot and Human Interactive Communication
ER -