AI Article Synopsis

  • This paper introduces an automatic method to reconstruct the surfaces of complex transparent objects using a dual-camera setup and laser scanning.
  • The approach identifies and categorizes 3D point candidates into first-reflection and non-first-reflection points, addressing the challenges posed by light transmission within transparent materials.
  • A four-layer refinement process is proposed to accurately extract first-reflection points, allowing for successful reconstruction of complex shapes of transparent objects compared to traditional methods.

Article Abstract

Acquiring the 3D geometry of objects has been an active research topic, wherein the reconstruction of transparent objects poses a great challenge. In this paper, we present a fully automatic approach for reconstructing the exterior surface of a complex transparent scene. Through scanning a line laser by a galvo-mirror, images of the scene are captured from two viewing directions. Due to the light transmission inside the transparent object, the captured feature points and the calibrated laser plane can produce large number of 3D point candidates with large incorrect points through direct triangulation. Various situations of laser transmission inside the transparent object are analyzed and the reconstructed 3D laser point candidates are classified into two types: first-reflection points and non-first-reflection points. The first-reflection points means the first reflected laser points on the front surface of measured objects. Then, a novel four-layers refinement process is proposed to extract the first-reflection points step by step from the 3D point candidates through optical geometric constraints, including (1) Layer-1 : fake points removed by single camera, (2) Layer-2 : ambiguity points removed by the dual-camera joint constraint, (3) Layer-3 : retrieve the missing first-reflection exterior surface points by fusion and (4) Layer-4 : severe ambiguity points removed by contour-continuity. Besides, a novel calibration model about this imaging system is proposed for 3D point candidates reconstruction through triangulation. Compared with traditional laser scanning method, we pulled in the viewing angle information of the second camera and a novel four-layers refinement process is adopted for reconstruction of transparent objects. Various experiments on real objects demonstrate that proposed method can successfully extract the first-reflection points from the candidates and recover the complex shapes of transparent and semitransparent objects.

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Source
http://dx.doi.org/10.1364/OE.449300DOI Listing

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