The National Science Foundation (NSF) awarded a $274,904 Small Business Innovation Research (SBIR) Phase I grant to Limar Ai Inc. on July 1, 2024 under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program. The objective of this project is to develop an integrated computer vision capability that combines geometric methods for constructing detailed 3D models from photographs with semantic methods for segmenting and classifying features or objects in 2D photographs. This integrated solution aims to dramatically improve the productivity, accuracy, and quality of information generated by surveyors and engineers charged with assessing, designing, and maintaining large-scale infrastructure such as utility poles, water systems, transportation networks, and other critical assets. The project integrates key technical challenges such as 2D-3D correspondence, computational efficiency, and user interfaces to enable effective infrastructure asset modeling, maintenance, and predictive analysis. The broader commercial impact of this work is to enhance the resilience, performance, and life-cycle management of the nation's critical infrastructure.
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