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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kodagoda, K.R.S. Alempijevic, A. Underwood, J. Kumar, S. Dissanayake, G. |
| Copyright Year | 2006 |
| Description | Author affiliation: Fac. of Eng., Technol. Univ., Sydney, NSW (Kodagoda, K.R.S.; Alempijevic, A.) |
| Abstract | Multimodal sensor registration and calibration are crucially important aspects in distributed sensor fusion. Unknown relationships of sensors and joint probability distribution between sensory signals make the sensor fusion nontrivial. In this paper, we adopt a Mutual Information (MI) based approach for sensor registration and calibration. It is based on unsupervised learning of a nonparametric sensing model by maximizing mutual information between signal streams. Experiments were carried out in an office like environment with two laser sensors capturing arbitrarily moving people. Attributes of the moving targets are used. Problems due to target occlusions are alleviated by the multiple model tracker. The registration and calibration methodology does not require any artificially generated patterns or motions unlike other calibration methodologies |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 621628 |
| Page Count | 6 |
| File Format | |
| ISBN | 1424403413 |
| DOI | 10.1109/ICARCV.2006.345361 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-12-05 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Calibration Sensor fusion Mutual information Sensor phenomena and characterization Multimodal sensors Probability distribution Unsupervised learning Laser fusion Laser modes Target tracking target tracking mutual information sensor registration sensor calibration IMM |
| Content Type | Text |
| Resource Type | Article |
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