Spectral 3D Computer Vision -- A Review
It provides a comprehensive survey for researchers and practitioners, but it is incremental as it synthesizes existing knowledge without introducing new methods or results.
This paper reviews spectral 3D computer vision, which integrates geometric and spectral data to enhance object understanding and representation, advancing traditional computer vision and enabling applications in fields like agriculture and cultural heritage.
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.