Online multi-object tracking via labeled random finite set with appearance learning

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Online multi-object tracking via labeled random finite set with appearance learning

© 2017 IEEE. In this paper, a novel approach to online multi-object tracking is proposed via Labeled Random Finite Sets (RFS) combined with appearance learning. The Labeled RFS formulation of the multi-object state naturally accommodates a time-varying number of objects, track labels, and false posi...

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Bibliographic Details
Main Author:	Kim, Du Yong
Format:	Conference Paper
Published:	2017
Online Access:	http://hdl.handle.net/20.500.11937/66632

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