Traditional helmet-mounted devices (HMDs), such as Night Vision Googles, are direct view systems where parallax, or image offset, is only along the line of sight and the impact to user performance is minimal. As HMDs transition to adding digital cameras while maintaining direct view capabilities, the sensor must be placed outside of the user’s line of sight. These offsets create more significant parallax and can greatly impact a user’s ability to navigate and to interact with objects at close distances. Parallax error can be easily corrected for a fixed distance to an object, but the error progressively increases when viewing objects that are closer or farther than the selected distance. More complicated methods can be employed, such as ground plane re-projection or correction based on a depth sensor, but those methods each have their own disadvantages. Factors such as alignment accuracy across the field of view and nauseating effects must also be considered. This paper describes the development of an image simulation representing parallax error in a virtual reality headset with the ability to apply different correction techniques with varying parameters. This simulation was used with a group of observers who were asked to move around a scene and qualitatively evaluate the effectiveness of each correction method with different combinations of sensors. Questions focused on their ability to complete certain tasks and their subjective experiences while using each method. Results from this evaluation are presented and recommendations are made for optimal settings and future studies.
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