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Fast inference of contaminated data for real time object tracking

Zhu, Hao; LI, Yi


The online object tracking is a challenging problem because any useful approach must handle various nuisances including illumination changes and occlusions. Though a lot of work focus on observation models by employing sophisticated approaches for contaminated data, they commonly assume that the samples for updating observation model are uncorrupted or can be restored in updating. For instance, in particle filter based approaches every particle has to be restored for each frame, which is...[Show more]

CollectionsANU Research Publications
Date published: 2015
Type: Conference paper
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI: 10.1007/978-3-319-16814-2_18


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