Augmenting the LSA technique to evaluate ubicomp environments

LSA is a useful user study technique, it is well known and used to design and evaluate Ubicomp systems. The LSA technique enables researchers to collect data, analyze it, and obtain quantitative and statistical results. A key advantage of using LSA is that it is performed in the user’s environment. However, analyzing large amounts of data is considered by some researchers to be a burden and time consuming, prone to human error. In this paper we explore the use of computer vision techniques to automate the data analysis and coding when using LSA. We present a system that uses facial tracking, object recognition and composite correlation filters to detect the Attention behavior of a subject. Our results indicate that computer vision can automate the LSA technique and reduce the burden of coding data manually by the researcher. The findings from this study reveal emergent practices of the use of our proposed system to automate the evaluation of Ubicomp environments.