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Open Access Tailored photometric stereo: Optimization of light source positions for various materials

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Industrial machine vision applications frequently employ Photometric Stereo (PS) methods to detect fine surface defects on objects with challenging surface properties. To achieve highly precise results, acquisition setups with a vast amount of strobed illumination angles are required. The time-consuming nature of such an undertaking renders it inapt for most industrial applications. We overcome these limitations by carefully tailoring the required light setup to specific applications. Our novel approach facilitates the design of optimized acquisition setups for inline PS inspection systems. The optimal positions of light sources are derived from only a few representative material samples without the need for extensive amounts of training data. We formulate an energy function that constructs the illumination setup which generates the highest PS accuracy. The setup can be tailored for fast acquisition speed or cost efficiency. A thorough evaluation of the performance of our approach will be given on a public data set, evaluated by the mean angular error (MAE) for surface normals and root mean square (RMS) error for albedos. Our results show, that the obtained optimized PS setups can deliver a reconstruction performance close to the ground truth, while requiring only a few acquisitions.
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Keywords: convex optimization; illumination; inline inspection; photometric stereo; surface reconstruction

Document Type: Research Article

Publication date: January 26, 2020

This article was made available online on January 26, 2020 as a Fast Track article with title: "Estimating vehicle fuel economy from overhead camera imagery and application for traffic control".

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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