Computer Vision Engineer (3D Reconstruction)

 Computer Vision Engineer (3D Reconstruction)

We are seeking a Computer Vision Engineer to develop a high-precision 3-D reconstruction and measurement systems utilizing Shape from Polarization ( SfP). In this role, you will bridge the gap between optical physics and geometry to extract submillimeter surface details from polarimetric data.

Crucial Skills (Must-Have Foundation)

● Solid understanding of the nature of polarized light and the use of the Stokes vector to
describe light states.
● Strong proficiency in linear algebra and vector calculus, particularly for coordinate
system transformations, 3D geometry, and extracting signals from noisy data.
● Fluency in Python (NumPy, SciPy) for data analysis and algorithm implementation.
● Experience with standard computer vision libraries for image filtering, alignment, and
feature detection, such as OpenCV and scikit-image.

Useful & Desirable Skills (Nice-to-Have)

● Familiarity with surface normals, depth maps, and Shape-from-X techniques (e.g.,
shading, stereo, or motion).
● Experience working with polarization cameras.
● Deep understanding of light reflection and scattering across different materials and
surface textures.
● Experience with normal integration approaches for 3D reconstruction to recover continuous surfaces.