Deep-learning enabled single-shot 3D feature detection in fringe projection profilometry

Juan C. Peña; Eberto Benjumea; Raúl Vargas; Lenny A. Romero; Alberto Patiño-Vanegas; Andres G. Marrugo

doi:10.1117/12.2663955

15 June 2023 Deep-learning enabled single-shot 3D feature detection in fringe projection profilometry

Juan C. Peña, Eberto Benjumea, Raúl Vargas, Lenny A. Romero, Alberto Patiño-Vanegas, Andres G. Marrugo

Proceedings Volume 12524, Dimensional Optical Metrology and Inspection for Practical Applications XII ; 1252404 (2023) https://doi.org/10.1117/12.2663955
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Reliably detecting or tracking 3D features is challenging. It often requires preprocessing and filtering stages, along with fine-tuned heuristics for reliable detection. Alternatively, artificial intelligence-based strategies have recently been proposed; however, these typically require many manually labeled images for training. We introduce a method for 3D feature detection by using a convolutional neural network and a single 3D image obtained by fringe projection profilometry. We cast the problem of 3D feature detection as an unsupervised detection problem. Hence, the goal is to use a neural network that learns to detect specific features in 3D images using a single unlabeled image. Therefore, we implemented a deep-learning method that exploits inherent symmetries to detect objects with few training data and without ground truth. Subsequently, using a pyramid methodology of rescaling each image to be processed, we achieved feature detections of different sizes. Finally, we unified the detections using a non-maximum suppression algorithm. Preliminary results show that the method provides reliable detection under different scenarios with a more flexible training procedure than other competing methods.

Conference Presentation

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Juan C. Peña, Eberto Benjumea, Raúl Vargas, Lenny A. Romero, Alberto Patiño-Vanegas, and Andres G. Marrugo "Deep-learning enabled single-shot 3D feature detection in fringe projection profilometry", Proc. SPIE 12524, Dimensional Optical Metrology and Inspection for Practical Applications XII , 1252404 (15 June 2023); https://doi.org/10.1117/12.2663955

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