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Poster Abstract: 3D Activity Localization With Multiple Sensors

We present a deep learning framework for fast 3D activity localization and tracking in a dynamic and crowded real world setting. Our training approach reverses the traditional activity localization approach, which first estimates the possible location of activities and then predicts their occurrence...

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Detalhes bibliográficos
Publicado no:IPSN
Main Authors: Li, Xinyu, Zhang, Yanyi, Zhang, Jianyu, Chen, Shuhong, Gu, Yue, Farneth, Richard A., Marsic, Ivan, Burd, Randall S.
Formato: Artigo
Idioma:Inglês
Publicado em: 2017
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6214452/
https://ncbi.nlm.nih.gov/pubmed/30393785
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1145/3055031.3055057
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