Clustering for Multi-Target Tracking
This thesis presents a clustering-based approach to decrease the computational cost of data association in multi-target tracking. This is achieved by clustering the sensor tracks using approximate distance functions, thereby decreasing the number of possible associations and the need to calculate ex...
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| Format: | Others |
| Language: | English |
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Linköpings universitet, Reglerteknik
2017
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-143807 |