Survey on classifying human actions through visual sensors
The ability to predict the intentions of people based solely on their visual actions is a skill only performed by humans and animals. This requires segmentation of items in the field of view, tracking of moving objects, identifying the importance of each object, determining the current role of each important object individually and in collaboration with other objects, relating these objects into a predefined scenario, assessing the selected scenario with the information retrieve, and finally adjusting the scenario to better fit the data. This is all accomplished with great accuracy in less than a few seconds. The intelligence of current computer algorithms has not reached this level of complexity with the accuracy and time constraints that humans and animals have, but there are several research efforts that are working towards this by identifying new algorithms for solving parts of this problem. This survey paper lists several of these efforts that rely mainly on understanding the image processing and classification of a limited number of actions. It divides the activities up into several groups and ends with a discussion of future needs.
visual human action classification artificial intelligence hidden markov model grammars