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- aggregation classification "C1".
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2014".
- aggregation format "application/pdf".
- aggregation hasFormat 5671222.bibtex.
- aggregation hasFormat 5671222.csv.
- aggregation hasFormat 5671222.dc.
- aggregation hasFormat 5671222.didl.
- aggregation hasFormat 5671222.doc.
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- aggregation isPartOf urn:isbn:9781479957514.
- aggregation language "eng".
- aggregation publisher "IEEE".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Technology and Engineering".
- aggregation title "A low resolution multi-camera system for person tracking".
- aggregation abstract "The current multi-camera systems have not studied the problem of person tracking under low resolution constraints. In this paper, we propose a low resolution sensor network for person tracking. The network is composed of cameras with a resolution of 30x30 pixels. The multi-camera system is used to evaluate probability occupancy mapping and maximum likelihood trackers against ground truth collected by ultra-wideband (UWB) testbed. Performance evaluation is performed on two video sequences of 30 minutes. The experimental results show that maximum likelihood estimation based tracker outperforms the state-of-the-art on low resolution cameras".
- aggregation authorList BK344115.
- aggregation endPage "490".
- aggregation startPage "486".
- aggregation aggregates 5671228.
- aggregation isDescribedBy 5671222.
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