Semantic Segmentation of Natural Materials on a Point Cloud Using Spatial and Multispectral Features.

ABSTRACT: The characterization of natural spaces by the precise observation of their material properties is highly demanded in remote sensing and computer vision. The production of novel sensors enables the collection of heterogeneous data to get a comprehensive knowledge of the living and non-living entities in the ecosystem. The high resolution of consumer-grade RGB cameras is frequently used for the geometric reconstruction of many types of environments. Nevertheless, the understanding of natural spaces is still challenging. The automatic segmentation of homogeneous materials in nature is a complex task because there are many overlapping structures and an indirect illumination, so the object recognition is difficult. In this paper, we propose a method based on fusing spatial and multispectral cha

SUBMITTER: Jurado JM 

PROVIDER: S-EPMC7218876 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature