Results 11 to 20 of about 3,692,483 (287)

Depth perception with gaze-contingent depth of field [PDF]

open access: yesProceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2014
Blur in images can create the sensation of depth because it emulates an optical property of the eye; namely, the limited depth of field created by the eye's lens. When the human eye looks at an object, this object appears sharp on the retina, but objects at different distances appear blurred.
Michael Mauderer 0001   +3 more
openaire   +5 more sources

A neural mechanism for detecting object motion during self-motion

open access: yeseLife, 2022
Detection of objects that move in a scene is a fundamental computation performed by the visual system. This computation is greatly complicated by observer motion, which causes most objects to move across the retinal image.
HyungGoo R Kim   +2 more
doaj   +1 more source

Transfer of Perceptual Learning From Local Stereopsis to Global Stereopsis in Adults With Amblyopia: A Preliminary Study

open access: yesFrontiers in Neuroscience, 2021
It has long been debated whether the analysis of global and local stereoscopic depth is performed by a single system or by separate systems. Global stereopsis requires the visual system to solve a complex binocular matching problem to obtain a coherent ...
Adrien Chopin   +11 more
doaj   +1 more source

Using Gaze-Contingent Depth of Field to Facilitate Depth Perception [PDF]

open access: yesi-Perception, 2014
The lens system of the human eye has a limited depth of field that creates blur patterns that depend on its focus and the relative distances of the observed objects.
M Mauderer   +3 more
doaj   +1 more source

The use of three-dimensional endoscope in transnasal skull base surgery: A single-center experience from China

open access: yesFrontiers in Surgery, 2022
ObjectiveThe development of skull base surgery in the past decade has been influenced by advances in visualization techniques; recently, due to such improvements, 3D endoscopes have been widely used.
Guo Xin   +8 more
doaj   +1 more source

Efficient Stereo Depth Estimation for Pseudo-LiDAR: A Self-Supervised Approach Based on Multi-Input ResNet Encoder

open access: yesSensors, 2023
Perception and localization are essential for autonomous delivery vehicles, mostly estimated from 3D LiDAR sensors due to their precise distance measurement capability.
Sabir Hossain, Xianke Lin
doaj   +1 more source

Two independent mechanisms for motion-in-depth perception : evidence from individual differences [PDF]

open access: yes, 2010
Our forward-facing eyes allow us the advantage of binocular visual information: using the tiny differences between right and left eye views to learn about depth and location in three dimensions.
Harold T Nefs   +11 more
core   +2 more sources

Why 2D layout in 3D images matters: evidence from visual search and eye-tracking

open access: yesJournal of Eye Movement Research, 2023
Precise perception of three-dimensional (3D) images is crucial for a rewarding experience when using novel displays. However, the capability of the human visual system to perceive binocular disparities varies across the visual field meaning that depth ...
Linda Krauze   +3 more
doaj   +1 more source

The development of active binocular vision under normal and alternate rearing conditions

open access: yeseLife, 2021
The development of binocular vision is an active learning process comprising the development of disparity tuned neurons in visual cortex and the establishment of precise vergence control of the eyes.
Lukas Klimmasch   +5 more
doaj   +1 more source

Binocular Information Improves the Reliability and Consistency of Pictorial Relief

open access: yesVision, 2022
Binocular disparity is an important cue to three-dimensional shape. We assessed the contribution of this cue to the reliability and consistency of depth in stereoscopic photographs of natural scenes. Observers viewed photographs of cluttered scenes while
Paul B. Hibbard   +2 more
doaj   +1 more source

Home - About - Disclaimer - Privacy