A numerical study of sensory-guided multiple views for improved object identification

B. A. Blakeslee; E. G. Zelnio; D. E. Koditschek

doi:10.1117/12.2050655

20 June 2014 A numerical study of sensory-guided multiple views for improved object identification

B. A. Blakeslee, E. G. Zelnio, D. E. Koditschek

Author Affiliations +

Proceedings Volume 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII; 909116 (2014) https://doi.org/10.1117/12.2050655
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

We explore the potential on-line adjustment of sensory controls for improved object identification and discrimination in the context of a simulated high resolution camera system carried onboard a maneuverable robotic platform that can actively choose its observational position and pose. Our early numerical studies suggest the significant efficacy and enhanced performance achieved by even very simple feedback-driven iteration of the view in contrast to identification from a fixed pose, uninformed by any active adaptation. Specifically, we contrast the discriminative performance of the same conventional classification system when informed by: a random glance at a vehicle; two random glances at a vehicle; or a random glance followed by a guided second look. After each glance, edge detection algorithms isolate the most salient features of the image and template matching is performed through the use of the Hausdor↵ distance, comparing the simulated sensed images with reference images of the vehicles. We present initial simulation statistics that overwhelmingly favor the third scenario. We conclude with a sketch of our near-future steps in this study that will entail: the incorporation of more sophisticated image processing and template matching algorithms; more complex discrimination tasks such as distinguishing between two similar vehicles or vehicles in motion; more realistic models of the observers mobility including platform dynamics and eventually environmental constraints; and expanding the sensing task beyond the identification of a specified object selected from a pre-defined library of alternatives.

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B. A. Blakeslee, E. G. Zelnio, and D. E. Koditschek "A numerical study of sensory-guided multiple views for improved object identification", Proc. SPIE 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII, 909116 (20 June 2014); https://doi.org/10.1117/12.2050655

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KEYWORDS

Light sources and illumination

Matrices

Control systems

Sensors

Cameras

Feature extraction

Performance modeling

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