  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.
