Abstract
This paper presents an approach for tracking multiple persons on a mobile robot with a combination of colour and thermal vision sensors, using several new techniques. First, an adaptive colour model is incorporated into the measurement model of the tracker. Second, a new approach for detecting occlusions is introduced, using a machine learning classifier for pairwise comparison of persons (classifying which one is in front of the other). Third, explicit occlusion handling is incorporated into the tracker. The paper presents a comprehensive, quantitative evaluation of the whole system and its different components using several real world data sets.
| Original language | English |
|---|---|
| Pages (from-to) | 435-443 |
| Number of pages | 9 |
| Journal | Robotics and Autonomous Systems |
| Volume | 58 |
| Issue number | 5 |
| DOIs | |
| State | Published - 31 May 2010 |
| Externally published | Yes |
Keywords
- AdaBoost
- Bayesian estimation
- Colour vision
- Occlusion detection
- Thermal vision
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