Recent Advances in Human Behaviour Understanding: A Survey

In our daily life we are trying to merge information and communication technology with our existing infrastructure to get right information at the right time. One way to reach this goal is to understanding human behaviour by capturing and analyzing real life data. Human behaviour understanding is an important issue to the researchers which is based on the various factors like human actions, activities, number of individuals, facial expressions, body posture and gestures, vocal characteristics, distance between the individuals, different weather conditions, work places, interactions and age groups. Different tools and technologies like geometric shape matching, artificial neural network, colour space analysis, Bayesian models, hidden markov model, Gaussian mixture model, support vector machine and deep learning can be used individually or can be combined together to solve this purpose. The concept can be applied in home, healthcare, transport, education, safety aid, entertainment, sports and many other places. This paper focuses on the evolution of technologies used for human behaviour understanding, divide them into different stages, find out the advantages and disadvantages and also discuss the important open research issues.