Spectral 3D Computer Vision -- A Review

TL;DR

Spectral 3D computer vision integrates spectral and geometric data to enhance understanding of physical object properties, advancing traditional methods and enabling diverse applications like agriculture and cultural heritage preservation.

Contribution

This survey provides a comprehensive overview and taxonomy of spectral 3D vision methods, highlighting its applications, challenges, and future research directions.

Findings

Unified taxonomy of spectral 3D methods

Identification of key application areas

Discussion of future challenges and prospects

Abstract

Spectral 3D computer vision examines both the geometric and spectral properties of objects. It provides a deeper understanding of an object's physical properties by providing information from narrow bands in various regions of the electromagnetic spectrum. Mapping the spectral information onto the 3D model reveals changes in the spectra-structure space or enhances 3D representations with properties such as reflectance, chromatic aberration, and varying defocus blur. This emerging paradigm advances traditional computer vision and opens new avenues of research in 3D structure, depth estimation, motion analysis, and more. It has found applications in areas such as smart agriculture, environment monitoring, building inspection, geological exploration, and digital cultural heritage records. This survey offers a comprehensive overview of spectral 3D computer vision, including a unified taxonomy of methods, key application areas, and future challenges and prospects.