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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Noyvirt, A. Renxi Qiu |
| Copyright Year | 2012 |
| Description | Author affiliation: School of Engineering, Cardiff University, UK (Noyvirt, A.; Renxi Qiu) |
| Abstract | A new method is proposed for using a combination of measurements from a laser range finder and a depth camera in a data fusion process that benefits from each modality's strong side. The combination leads to a significantly improved performance of the human detection and tracking in comparison with what is achievable from the singular modalities. The useful information from both laser and depth camera is automatically extracted and combined in a Bayesian formulation that is estimated using a Markov Chain Monte Carlo (MCMC) sampling framework. The experiments show that this algorithm can track robustly multiple people in real world assistive robotics applications. |
| Starting Page | 1176 |
| Ending Page | 1181 |
| File Size | 309074 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467303125 |
| e-ISBN | 9781467303118 |
| DOI | 10.1109/INDIN.2012.6301153 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-07-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bayesian methods Humans Measurement by laser beam human detection service robotics Detectors human tracking MCMC Robot sensing systems Cameras sensor data fusion assistive technology |
| Content Type | Text |
| Resource Type | Article |
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