Publication Type:

Conference Paper

Source:

2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, Jaipur, India (2016)

URL:

https://ieeexplore.ieee.org/abstract/document/7732174

Keywords:

Automata, computational modeling, Computer science, concurrent activity recognition, Data structures, Electronic mail, finite state automata, finite state machines, FSM based methodology, Hidden Markov models, Informatics, interleaved activity recognition, Object recognition, queue data structures, sequential human activity recognition, stack data structures

Abstract:

Research on human activity recognition is one of the most promising research topic and is attracted attention towards a number of disciplines and application domains. Successful research has so far focused on recognizing sequential human activities. In real life people are performing actions not only in sequential but also in complex (concurrent or interleaved) manner. Recognizing complex activities remains a challenging and active area of research. Due to a high degree of freedom of human activities, it is difficult to have a model which can deal with interleaved and concurrent activities. We propose a method that uses automatically constructed finite state automata, stack and queue data structures for recognizing concurrent and interleaved activities.

Cite this Research Publication

J. Kavya and M. Geetha, “An FSM based methodology for interleaved and concurrent activity recognition”, in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, 2016.