Visualization of Targets Invisible Due to Atmospheric Conditions

When conditions prevent mechanical or visual scanning of environments and providing of situational awareness using vision-based technologies, there need to be alternatives. The goal of this research is to provide users (decision makers such as pilots, drivers of cars or vehicles, operators of equipment at night or in blizzard conditions) an accurate visualization of the real-time conditions of a moving machine (e.g., automobile, aircraft, tank, truck) when the surrounding atmosphere is entirely or nearly opaque or the light conditions are not favorable for use of vision-based sensors.

Although identified/scored as an aviation-industry specific topic, the scope of this topic is very broad and results could be applied in many industries (e.g., automotive). The topic spans everything from the use of non-visual sensors (e.g., sonar) for depth to the development of new computer-human interfaces for 3D data visualization.

Stakeholders

AR experience developers, operators and owners/users of commercial, private or military aircraft

Possible Methodologies

Acquisition and/or development of lightweight and power-efficient infrared sensors that are effective as alternatives to cameras and existing vision-based environmental capture. Testing and development of 3D interaction modes when user’s natural vision is impaired. This research topic could explore IR sensors (which measure differences in temperature, also known as “thermal imaging”), as well as new alternatives.

Research Program

This topic of research overlaps with the topic of using AR to visualize any stationary or moving object in low-visibility conditions. The outcomes of this research could also be applied in non-industrial use cases (e.g., skiing or other sports in low visibility-conditions). The same research topic could be combined with study of user interfaces and interaction paradigms for the visually impaired community.

Miscellaneous Notes

The use of night vision technologies is widespread in the military/defense industry. There have also been studies of the use of AR for air traffic control.

Keywords

Situational awareness, night vision, non-visual scanning in real time, aviation and aerospace, military, reconnaissance, occlusion, depth of field, automotive, sensor fusion, data layers, ToF (Time of Flight) sensors, computer vision, autonomous vehicles, user experience, night vision, aircraft navigation, avionics, aircraft displays, air navigation, aircraft detection, automotive, user experience

Research Agenda Categories

Industries, Displays, Technology

Expected Impact Timeframe

Medium

Related Publications

Using the words in this topic description and Natural Language Processing analysis of publications in the AREA FindAR database, the references below have the highest number of matches with this topic:

• Ciocoiu, T. I., & Moldoveanu, F. D. (2017). Vision based localization stereo rig calibration and rectification. 2017 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) & 2017 Intl Aegean Conference on Electrical Machines and Power Electronics (ACEMP).
• He, Y., & Chen, S. (2019). Recent Advances in 3D Data Acquisition and Processing by Time-of-Flight Camera. IEEE Access, 7, 12495-12510.
• Pascoal, R. M., de Almeida, A., & Sofia, R. C. (2019). Activity recognition in outdoor sports environments. Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers.
• Zhao, Y., Kupferstein, E., Castro, B. V., Feiner, S., & Azenkot, S. (2019). Designing AR Visualizations to Facilitate Stair Navigation for People with Low Vision. Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology.
• Park, Y. J., Ro, H., Byun, J.-H., & Han, T.-D. (2019). Adaptive projection augmented reality with object recognition based on deep learning. Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion.

More publications can be explored using the AREA FindAR research tool.

Author

Christine Perey

Last Published (yyyy-mm-dd)

2021-08-31

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