Eye Movement Analysis in Visual Inspection of Geospatial Data

Modern geospatial data acquisition systems deliver vast amounts of multi-domain remotely sensed data such as multi/hyper spectral imagery and LIDAR point-clouds. Unfortunately geospatial products automatically derived from source geospatial data are burdened with residual errors and artifacts which should be manually inspected, cleaned and corrected. These tasks become critical in many large-scale projects that require real-time processing of immense amounts of visual information and usually require manual post-processing or visual inspection of the source and/or derived data. The process of visual inspection could be divided in two general phases: perception and reaction. Scene perception comprises several steps such as visual search, feature selection and identification. Reaction reflects a decision made by an operator and usually involves other types of modalities (e.g. physical action such as mouse movements or typing). Human analysts perceive visual data through intensive movements of eyes which subconsciously select the most distinctive features in an image in order to reduce our overall ambiguity about the observed scene. A sequence of eye movements may then be understood within a framework of sequential accumulation of information. Whether or not all informative points are detected depends on both the observer’s current knowledge of the stimulus and the particular task. Dynamics of this information accrual process can be documented and quantified using analysis of eye movements during the process of natural, active visual perception. This paper presents theoretical and practical investigations that have been made to illustrate the feasibility of 3D gaze tracking as a disambiguation tool in the process of visual search of a target in high resolution imagery.