BALANCING BETWEEN COMPUTER AND MACHINE VISION - A DESCRIPTION OF AN IMAGERY TOOLCHAIN FOR COMPLEX SOLUTIONS

Machine learning (ML), artificial intelligence (AI), and computational photography (CP) are pushing the boundaries of how electro-optical (EO) and infra-red (IR) sensors are being used. Especially within military environments, users are asking much more from EO and IR sensor suites. While hardware capability continues to advance the state of the art, software has become the true differentiator for how well these sensor platforms perform for the warfighter. This paper presents work that Consolidated Resource Imaging (CRI) has been developing in the areas of machine learning and computational photography. In this effort, we will discuss two areas of understanding: imagery meant for machine vision and imagery meant for human consumption. We will show how the intersection of machine learning and computational photography allow the symbiotic relationship between the human and the computer.

Citation: A. Paul Skentzos, B. Stephen Pizzo, “Balancing Between Computer and Machine Vision – A Description of an Imagery Toolchain for Complex Solutions”, In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 11-13, 2020.