TY - JOUR
T1 - Fuzzy human motion analysis
T2 - a review
AU - Lim, Chern Hong
AU - Vats, Ekta
AU - Chan, Chee Seng
N1 - Funding Information:
This research is supported by the High Impact Research MoE Grant UM.C/625/1/HIR/MoE/FCSIT/08 , H-22001-00-B0008 from the Ministry of Education Malaysia.
Publisher Copyright:
© 2014 Elsevier Ltd. All rights reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - Human Motion Analysis (HMA) is currently one of the most popularly active research domains as such significant research interests are motivated by a number of real world applications such as video surveillance, sports analysis, healthcare monitoring and so on. However, most of these real world applications face high levels of uncertainties that can affect the operations of such applications. Hence, the fuzzy set theory has been applied and showed great success in the recent past. In this paper, we aim at reviewing the fuzzy set oriented approaches for HMA, individuating how the fuzzy set may improve the HMA, envisaging and delineating the future perspectives. To the best of our knowledge, there is not found a single survey in the current literature that has discussed and reviewed fuzzy approaches towards the HMA. For ease of understanding, we conceptually classify the human motion into three broad levels: Low-Level (LoL), Mid-Level (MiL), and High-Level (HiL) HMA.
AB - Human Motion Analysis (HMA) is currently one of the most popularly active research domains as such significant research interests are motivated by a number of real world applications such as video surveillance, sports analysis, healthcare monitoring and so on. However, most of these real world applications face high levels of uncertainties that can affect the operations of such applications. Hence, the fuzzy set theory has been applied and showed great success in the recent past. In this paper, we aim at reviewing the fuzzy set oriented approaches for HMA, individuating how the fuzzy set may improve the HMA, envisaging and delineating the future perspectives. To the best of our knowledge, there is not found a single survey in the current literature that has discussed and reviewed fuzzy approaches towards the HMA. For ease of understanding, we conceptually classify the human motion into three broad levels: Low-Level (LoL), Mid-Level (MiL), and High-Level (HiL) HMA.
KW - Action recognition
KW - Fuzzy set theory
KW - Human motion analysis
UR - http://www.scopus.com/inward/record.url?scp=84921772594&partnerID=8YFLogxK
U2 - 10.1016/j.patcog.2014.11.016
DO - 10.1016/j.patcog.2014.11.016
M3 - Article
AN - SCOPUS:84921772594
SN - 0031-3203
VL - 48
SP - 1773
EP - 1796
JO - Pattern Recognition
JF - Pattern Recognition
IS - 5
ER -
