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This paper presents a novel three-dimensional (3-D) eye movement analysis algorithm for binocular eye tracking within virtual reality (VR). The user's gaze direction, head position, and orientation are tracked in order to allow recording of the user's fixations within the environment. Although the linear signal analysis approach is itself not new, its application to eye movement analysis in three dimensions advances traditional two-dimensional approaches, since it takes into account the six degrees of freedom of head movements and is resolution independent. Results indicate that the 3-D eye movement analysis algorithm can successfully be used for analysis of visual process measures in VR. Process measures not only can corroborate performance measures, but also can lead to discoveries of the reasons for performance improvements. In particular, analysis of users' eye movements in VR can potentially lead to further insights into the underlying cognitive processes of VR subjects.

a) User interface. (b) Eye image from (c) 3D scanpaths. tracking device.Figure 1: Recording binocular eye movements in aircraft cargo bay virtual inspection environment. AbstractThis paper describes the development of a binocular eye tracking Virtual Reality system for aircraft inspection training. The aesthetic appearance of the environment is driven by standard graphical techniques augmented by realistic texture maps of the physical environment. A "virtual flashlight" is provided to simulate a tool used by inspectors. The user's gaze direction, as well as head position and orientation, are tracked to allow recording of the user's gaze locations within *

A study was conducted to measure the effects of human trust and to determine how it develops over time in a hybrid inspection system given different types of errors (i.e., false alarms and misses). The study also looked at which of the four dimensions of trust (competence, predictability, reliability, and faith) were the best predictors of overall trust. Results from the study showed that trust is sensitive to the type of errors made by a system. There was a significant change in overall trust between the stages for the conservative and risky systems, but no significant change in the neutral system. In regards to the best predictors of trust, faith appeared as one of the predictors in all three trial blocks for the conservative and risky systems. As time progressed, predictability emerged in the second and third trial blocks for the conservative system. Competence played an important role in the development of trust for the risky system, whereas reliability played an important role for the neutral system. These results suggest that subjective ratings of trust and the properties of the system can be used to predict the allocation of functions in hybrid inspection systems.

Research in the area of visual inspection has shown that various factors influence inspection performance. Task factors have been identified as one of the primary classes of factors influencing the complexity of inspection tasks. If inspection task complexity is to be reduced it is essential to understand the influence of various task factors and prescribe interventions based on the impact of these factors. Moreover, historical work in this area has shown that the greater the difficulty of a vigilance task, the more engaged operators may become. Therefore, this research studies the influence of the following task factors: number of defect types, defect standard complexity, defect probability, and defect distribution on both the visual search and decision-making components of a contact lens inspection task. This study was conducted using a computer simulation of a real world contact lens inspection task using 28 student subjects. Performance was measured on both the visual search and decision-making components of the task. The results revealed a negative influence of defect standard complexity and a positive influence of defect probability on both the visual search and decision-making components of the inspection task.