Skill Metrics for Mobile Crane Operators Based on Gaze Fixation Pattern

This paper proposes skill metrics that analyzes the gaze fixation pattern of mobile crane operators. This study focuses on the fixation data because they commonly represent visual information processing. First, scenes of crane operation are divided into content-based Area of Interests (AOIs) and the Markov Chains is used to model the gaze transitions between these AOIs. Four metrics were introduced to interpret the model at different expertise levels. Results suggest that experienced operators exhibit lower metrics compared to their novice counterparts, and adapted entropy measures exhibit similar patterns as the original ones in the previous study. Most importantly, the proposed metrics are able to address the following issues, i.e. large and sparse model, as highlighted in the previous study.