Abstract Low Rank Regularization (LRR), in essence, involves introducing a low rank or
approximately low rank assumption to target we aim to learn, which has achieved great …

Acquiring high-resolution 3D surface structures is a crucial task in computer vision as it
provides more detailed surface textures and clearer structures. Photometric stereo can …

Photometric stereo recovers three-dimensional (3D) object surface normal from multiple
images under different illumination directions. Traditional photometric stereo methods suffer …

Laser triangulation and photometric stereo are commonly used three-dimensional (3-D)
reconstruction methods, but they bear limitations in an underwater environment. One …

Classical photometric stereo requires uniform collimated light, but point light sources are
usually employed in practical setups. This introduces errors to the recovered surface shape …

Photometric stereo is one common surface normal estimation technique, which can be
utilized for various industrial tasks such as 3-D surface detail reconstruction and defect …

Due to different materials, product surfaces are susceptible to light, shadow, reflection, and
other factors. Coupled with the appearance of defects of various shapes and types, as well …

Multi-instance learning (MIL) has been extensively applied to various real tasks involving
objects with bags of instances, such as in drugs and images. Previous studies on MIL …

Photometric Stereo (PS) techniques have been developed accounting for several material
and surface characteristics. While various methods have achieved high accuracy, this has …

Cette thèse s' intéresse à la reconstruction 3D par stéréophotométrie et à la vision
omnidirectionnelle. La stéréophotométrie repose sur l'exploitation de plusieurs …