A HMM Framework for Motion based parsing for video from Observational Psychology

Abstract

In Psychology it is common to conduct studies involving the observation of humans undertaking some task. The sessions are typically recorded on video and used for subjective visual analysis. The subjective analysis is tedious and time consuming, not only because much useless video material is recorded but also because subjective measures of human behaviour are not necessarily repeatable. This paper presents a HMM framework for content based video analysis to facilitate the automated parsing of video from one such study involving Dyslexia. The framework relies on implicit measures of human motion that can be generalised to other applications in the domain of human observation.