The increasing number and complexity of operational sensors (radar, infrared, hyperspectral...) and availability of huge amount of data, lead to more and more sophisticated information presentations. But one key element of the IMINT line cannot be improved beyond initial system specification: the operator....
In order to overcome this issue, we have to better understand human visual object representation.
Object recognition theories in human vision balance between matching 2D templates representation with viewpoint-dependant information, and a viewpoint-invariant system based on structural description. Spatial frequency content is relevant due to early vision filtering. Orientation in depth is an important variable to challenge object constancy.
Three objects, seen from three different points of view in a natural environment made the original images in this study. Test images were a combination of spatial frequency filtered original images and an additive contrast level of white noise.
In the first experiment, the observer's task was a same versus different forced choice with spatial alternative. Test images had the same noise level in a presentation row. Discrimination threshold was determined by modifying the white noise contrast level by means of an adaptative method.
In the second experiment, a repetition blindness paradigm was used to further investigate the viewpoint effect on object recognition.
The results shed some light on the human visual system processing of objects displayed under different physical descriptions. This is an important achievement because targets which not always match physical properties of usual visual stimuli can increase operational workload.