Stereoscopic depth perception through foliage.
Sci Rep
; 14(1): 23056, 2024 10 04.
Article
em En
| MEDLINE
| ID: mdl-39367044
ABSTRACT
Both humans and computational methods struggle to discriminate the depths of objects hidden beneath foliage. However, such discrimination becomes feasible when we combine computational optical synthetic aperture sensing with the human ability to fuse stereoscopic images. For object identification tasks, as required in search and rescue, wildlife observation, surveillance, and early wildfire detection, depth assists in differentiating true from false findings, such as people, animals, or vehicles vs. sun-heated patches at the ground level or in the tree crowns, or ground fires vs. tree trunks. We used video captured by a drone above dense woodland to test users' ability to discriminate depth. We found that this is impossible when viewing monoscopic video and relying on motion parallax. The same was true with stereoscopic video because of the occlusions caused by foliage. However, when synthetic aperture sensing was used to reduce occlusions and disparity-scaled stereoscopic video was presented, whereas computational (stereoscopic matching) methods were unsuccessful, human observers successfully discriminated depth. This shows the potential of systems which exploit the synergy between computational methods and human vision to perform tasks that neither can perform alone.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Percepção de Profundidade
Limite:
Humans
Idioma:
En
Revista:
Sci Rep
/
Sci. rep. (Nat. Publ. Group)
/
Scientific reports (Nature Publishing Group)
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Áustria
País de publicação:
Reino Unido