the Synthetic Sensation Approach to Information Integration (SSAII) - - PowerPoint PPT Presentation

the synthetic sensation approach to information
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the Synthetic Sensation Approach to Information Integration (SSAII) - - PowerPoint PPT Presentation

CERI Workshop Presentation Human Research and Engineering Directorate Imagery Analysis Enhancement by the Synthetic Sensation Approach to Information Integration (SSAII) Bruce Hunn AMSRD-ARL-HR-MY Ft Huachuca Field Element May 13,2008


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Human Research and Engineering Directorate

Imagery Analysis Enhancement by the Synthetic Sensation Approach to Information Integration (SSAII)

Bruce Hunn AMSRD-ARL-HR-MY Ft Huachuca Field Element May 13,2008

CERI Workshop Presentation

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Human Research and Engineering Directorate

How do we learn and identify objects? I suggest that we learn naturalistically by a fused synthesis process where natural sensation bandwidths, are combined cognitively to form a cohesive, mental model. However, current technology has provided isolated bandwidth representations which are then cognitively forced, in a serial fashion, into a mental model. Background: Sensation and Perception

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Human Research and Engineering Directorate

Technology advancements in sensor fusion have allowed jet aircraft pilots to enhance their situation awareness and effectiveness because of fused sensor systems...why has this concept not been applied to other systems?

CERI 2008

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Human Research and Engineering Directorate

Current Imagery systems are individual, separate, and require divided attention, and cognitive synthesis to be fused into a cohesive concept

They are characterized by distinct bandwidth limits, each of which provides information, but all of which provide information which must be serially merged through cognitive processes into a cohesive single concept. IR (Infrared) EO (Electro-optical) Radar Radio

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Human Research and Engineering Directorate

What would be the outcome if three or four, current visual imagery systems could be merged into one and enhanced by sensor fusion? An analogy…

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Human Research and Engineering Directorate

Two types of Predators

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Human Research and Engineering Directorate

Two types of Predator vision

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Human Research and Engineering Directorate

Multi-band Single-band Fused Separate Integrated Iconic Realistic Realistic & Virtual

Features: Two types of Predator vision

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Human Research and Engineering Directorate

Current, separate, vision technologies

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Human Research and Engineering Directorate

Human Factors Challenges: High resolution imagery for all systems needed The equivalent of Geo-Rectification (pattern matching) of multiple bands into a cohesive, realistic, single, image. Selection of intuitive color scheme for band identification Consideration of auditory input as a diversification and redundant coding method

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Human Research and Engineering Directorate

Application example

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Human Research and Engineering Directorate

Challenge Provide a visual, synthetic system that combines current technology sensors into an integrated visual product, fusing data into a model that is both cognitively intuitive and powerful.

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Human Research and Engineering Directorate

United States Army Research Lab Bruce Hunn AMSRD-ARL-HR-MY US Army Research Laboratory 2520 Healy Ave. Ste 1172 (Bldg 51005) Ft Huachuca, AZ 85613-7069 520-538-4701 DSN 879-4701 FAX 520-538-0845