Biomimetic fusion that enhances sensor performance in a bimodal surveillance system

Leah Ziph-Schatzberg; Sarah Kelsall; Allyn E. Hubbard

doi:10.1117/12.883399

23 May 2011 Biomimetic fusion that enhances sensor performance in a bimodal surveillance system

Leah Ziph-Schatzberg, Sarah Kelsall, Allyn E. Hubbard

Proceedings Volume 8046, Unattended Ground, Sea, and Air Sensor Technologies and Applications XIII; 804609 (2011) https://doi.org/10.1117/12.883399
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

Algorithms for synergistically fusing acoustic and optical sensory inputs, thereby mimicking biological attentional processes are described. Manual existing perimeter defense surveillance systems using more than one sensory modality combine different sensors' information to corroborate findings by other sensors and to add data from a second modality. In contrast to how conventional systems work, animals use information from multiple sensory inputs in a way that improves each sensory system's performance. We demonstrated that performance is enhanced when information in one modality is used to focus processing in the other modality (a form of attention). This synergistic bi-modal operation improves surveillance efficacy by focusing auditory and visual "attention" on a particular target or location. Algorithms for focusing auditory and visual sensors using detection information were developed. These combination algorithms perform "zoom-with-enhanced-acuity" in both the visual and auditory domains, triggered by detection in either domain. Sensory-input processing algorithms focus on specific locations, indicated by at least one of the modalities. This spatially focused processing emulates biological attention-driven focusing. We showed that given information about the target, the acoustic algorithms were able to achieve over 80% correct target detection at signal-tonoise ratios (SNRs) of -20 dB and above, as compared with similar performance at SNRs of -10 db and above without target information from another modality. Similarly, the visual algorithm achieved performance of over 80% detection with added noise variance of 0.001 without target indication, but maintained 100% detection at added noise variance of 0.05 when acoustic target information was taken into account.

Citation Download Citation

Leah Ziph-Schatzberg, Sarah Kelsall, and Allyn E. Hubbard "Biomimetic fusion that enhances sensor performance in a bimodal surveillance system", Proc. SPIE 8046, Unattended Ground, Sea, and Air Sensor Technologies and Applications XIII, 804609 (23 May 2011); https://doi.org/10.1117/12.883399

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KEYWORDS

Detection and tracking algorithms

Target detection

Sensors

Video

Visualization

Algorithm development

Signal to noise ratio

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