Name
Abstract | ||
|---|---|---|
Detection of multiple people is a key element for social robot design and it is a requirement for effective human-robot interaction. However, it is not an easy task, especially in complex real world scenarios that commonly involve unpredictable motion of people. This paper focuses on detecting multiple people with a mobile robot by fusing information from different sensors over time. The proposed approach applies a segmentation method that uses the distance to the objects to separate possible people from the background and a novel adaptive contour people model to obtain a probability of detecting people. A probabilistic skin model is also applied to the images and both evidences are merged and used over time with a Bayesian scheme to detect people. We present experimental results that demonstrate how the proposed method is able to detect people who is standing, sitting and leaning sideways using a mobile robot in cluttered real world scenarios. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-16952-6_53 | IBERAMIA |
Keywords | Field | DocType |
dynamic indoor environment,multiple people,complex real world scenario,mobile robot,social robot design,possible people,novel adaptive contour people,cluttered real world scenario,probabilistic skin model,probability of detection,social robot,human robot interaction | Social robot,Computer vision,Computer science,Segmentation,Artificial intelligence,Mobile robot navigation,Probabilistic logic,Mobile robot,Bayesian probability | Conference |
Volume | ISSN | ISBN |
6433 | 0302-9743 | 3-642-16951-1 |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Alberto Méndez-Polanco | 1 | 3 | 0.77 |
| Angélica Muñoz-Meléndez | 2 | 44 | 10.51 |
| Eduardo F. Morales | 3 | 559 | 57.67 |