scholarly journals A moving observer in a three-dimensional world

2016 ◽  
Vol 371 (1697) ◽  
pp. 20150265 ◽  
Author(s):  
Andrew Glennerster
Keyword(s):  
Visual Information ◽  
Reference Frames ◽  
Three Dimensional ◽  
Local Shape ◽  
Dimensional Reconstruction ◽  
The Face ◽  
Three Dimensional Coordinate ◽  
Three Dimensional Vision ◽  
The Brain ◽  
Speed And Accuracy

For many tasks such as retrieving a previously viewed object, an observer must form a representation of the world at one location and use it at another. A world-based three-dimensional reconstruction of the scene built up from visual information would fulfil this requirement, something computer vision now achieves with great speed and accuracy. However, I argue that it is neither easy nor necessary for the brain to do this. I discuss biologically plausible alternatives, including the possibility of avoiding three-dimensional coordinate frames such as ego-centric and world-based representations. For example, the distance, slant and local shape of surfaces dictate the propensity of visual features to move in the image with respect to one another as the observer's perspective changes (through movement or binocular viewing). Such propensities can be stored without the need for three-dimensional reference frames. The problem of representing a stable scene in the face of continual head and eye movements is an appropriate starting place for understanding the goal of three-dimensional vision, more so, I argue, than the case of a static binocular observer. This article is part of the themed issue ‘Vision in our three-dimensional world’.

scholarly journals Cinematic rendering of a burst sagittal suture caused by an occipito-frontal gunshot wound

2021 ◽  
Author(s):  
Dominic Gascho ◽  
Michael J. Thali ◽  
Rosa M. Martinez ◽  
Stephan A. Bolliger
Keyword(s):  
Gunshot Wound ◽  
Three Dimensional ◽  
The Novel ◽  
Sagittal Suture ◽  
Resonance Imaging ◽  
Cinematic Rendering ◽  
Reconstruction Methods ◽  
Dimensional Reconstruction ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain

AbstractThe computed tomography (CT) scan of a 19-year-old man who died from an occipito-frontal gunshot wound presented an impressive radiating fracture line where the entire sagittal suture burst due to the high intracranial pressure that arose from a near-contact shot from a 9 mm bullet fired from a Glock 17 pistol. Photorealistic depictions of the radiating fracture lines along the cranial bones were created using three-dimensional reconstruction methods, such as the novel cinematic rendering technique that simulates the propagation and interaction of light when it passes through volumetric data. Since the brain had collapsed, depiction of soft tissue was insufficient on CT images. An additional magnetic resonance imaging (MRI) examination was performed, which enabled the diagnostic assessment of cerebral injuries.

Expectedness

2017 ◽  
Author(s):  
Jerome Kagan
Keyword(s):  
Semantic Category ◽  
Locus Ceruleus ◽  
Unexpected Event ◽  
Psychological States ◽  
The Face ◽  
The Difference ◽  
The One ◽  
Oscillation Frequencies ◽  
The Brain ◽  
Speed And Accuracy

This chapter analyzes how subject expectations affect all brain measures. An expectation of pain, a difficult task, an unpleasant picture, an air puff to the face, the sound of hands clapping, a metaphorical sentence, a caress, cocaine, an exemplar of a semantic category, or the benefit of a medicine each affects brain profiles as well as the speed and accuracy of perceptions. Meanwhile, unexpected events activate many brain sites, but especially the amygdala, hippocampus, prefrontal cortex, ventral tegmental area, and locus ceruleus. The difference in the oscillation frequencies evoked by the event anticipated and the one that occurs may be a critical cause of these activations. The brain and psychological states generated by an unexpected event depend on its desirability and familiarity.

scholarly journals WHISKiT Physics: A three-dimensional mechanical model of the rat vibrissal array

2019 ◽  
Author(s):  
Nadina O. Zweifel ◽  
Nicholas E. Bush ◽  
Ian Abraham ◽  
Todd D. Murphey ◽  
Mitra J.Z. Hartmann
Keyword(s):  
Three Dimensional ◽  
Simulation Framework ◽  
Mechanical Signals ◽  
Somatosensory Information ◽  
Tactile Input ◽  
Input Signals ◽  
The Face ◽  
Whisker Stimulation ◽  
The Brain ◽  
Behavioral Conditions

AbstractRodents tactually explore the environment using ~62 whiskers (vibrissae), regularly arranged in arrays on both sides of the face. The rat vibrissal system is one of the most commonly used models to study how the brain encodes and processes somatosensory information. To date, however, researchers have been unable to quantify the mechanosensory input at the base of each whisker, because the field lacks accurate models of three-dimensional whisker dynamics. To close this gap, we developed WHISKiT Physics, a simulation framework that incorporates realistic morphology of the full rat whisker array to predict time-varying mechanical signals for all whiskers. The dynamics of single whiskers were optimized based on experimental data, and then validated against free tip oscillations and the dynamic response to collision. The model is then extrapolated to include all whiskers in the array, taking into account each whisker’s individual geometry. Simulations of first mode resonances across the array approximately match previous experimental results and fall well within the range expected from biological variability. Finally, we use WHISKiT Physics to simulate mechanical signals across the array during three distinct behavioral conditions: passive whisker stimulation, active whisking against two pegs, and active whisking in a natural environment. The results demonstrate that the simulation system can be used to predict input signals during a variety of behaviors, something that would be difficult or impossible in the biological animal. In all behavioral conditions, interactions between array morphology and individual whisker geometry shape the tactile input to the whisker system.

scholarly journals The volume fraction values of the brain compartments using the Cavalieri principle and a 3T MRI in brachycephalic and mesocephalic dogs

2019 ◽  
Vol 64 (No. 11) ◽  
pp. 482-489
Author(s):  
C Bakici ◽  
RO Akgun ◽  
D Ozen ◽  
O Alagin ◽  
C Oto
Keyword(s):  
Magnetic Resonance ◽  
Volume Fraction ◽  
Third Ventricle ◽  
Three Dimensional ◽  
Cerebral Aqueduct ◽  
Point Counting ◽  
Brain Ventricles ◽  
Cavalieri Principle ◽  
Dimensional Reconstruction ◽  
The Brain

This study was aimed at: 1) estimating the volume and the volume fraction values of brain ventricles, grey matter and white matter with the Cavalieri principle and 2) creating three-dimensional reconstruction models of the brain ventricles by using magnetic resonance imaging. The brain structures of dogs were scanned with a 3T magnetic resonance system. The volumes of the total brain, the grey matter, the white matter, the lateral ventricle, the third ventricle, the cerebral aqueduct and the fourth ventricle of both sides were estimated separately by using a combination of the Cavalieri principle and the point-counting method. In addition to that, magnetic resonance images of dog brains were uploaded to the 3D slicer software to design the three-dimensional reconstruction models. The mean volume fraction values of the left and right lateral ventricle, third ventricle, cerebral aqueduct, and fourth ventricle were 1.83 ± 0.14%, 1.75 ± 0.1%, 0.7 ± 0.07%, 0.2 ± 0.04%, and 1 ± 0.32% for the brachycephalic dogs and 1.69 ± 0.04%, 1.66 ± 0.03%, 0.91 ± 0.03%, 0.27 ± 0.05%, and 0.71 ± 0.15% for the mesocephalic dogs, respectively. There was no statistically significant difference between the brachycephalic and mesocephalic dogs in all the volume fraction values (P > 0.05). This study showed the volume and the volume fraction values of the brain ventricles and the structures in the different types of the dogs’ head shapes. These volume fraction values can be essential data for determining some diseases. Magnetic resonance imaging can be used for precise volume estimations in combination with the Cavalieri principle and the point-counting method.

The Reconstruction for Han Dynasty Stone Images Based on Three-Dimensional Vision

2014 ◽  
Vol 556-562 ◽  
pp. 5009-5012
Author(s):  
Guang Dong Pan
Keyword(s):  
Mathematical Model ◽  
3D Reconstruction ◽  
Basic Principle ◽  
Projective Transformation ◽  
Three Dimensional ◽  
Reconstruction Algorithm ◽  
Han Dynasty ◽  
Dimensional Reconstruction ◽  
New Research ◽  
Three Dimensional Vision

Mainly studying the three-dimensional reconstruction for multiple Han Dynasty stone images, this paper proposes a 3D reconstruction algorithm based on two images. The author analyzes the basic principle of SIFT matching points detection according to Epipolar geometry constraints and projective transformation of images in 2D plane, and establishes mathematical model for the 3D reconstruction on foundation of sequence images. The feasibility of 3D reconstruction based on the sequence images is approved by simulation for three gray-scale Han Dynasty stone digital images which provides a new research way for identifying the feature of a target by the camera.

scholarly journals Computations underlying the visuomotor transformation for smooth pursuit eye movements

2015 ◽  
Vol 113 (5) ◽  
pp. 1377-1399 ◽  
Author(s):  
T. Scott Murdison ◽  
Guillaume Leclercq ◽  
Philippe Lefèvre ◽  
Gunnar Blohm
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Reference Frames ◽  
Three Dimensional ◽  
Head Orientation ◽  
Smooth Pursuit Eye Movements ◽  
Visuomotor Transformation ◽  
Pursuit Eye Movements ◽  
Retinal Motion ◽  
The Brain

Smooth pursuit eye movements are driven by retinal motion and enable us to view moving targets with high acuity. Complicating the generation of these movements is the fact that different eye and head rotations can produce different retinal stimuli but giving rise to identical smooth pursuit trajectories. However, because our eyes accurately pursue targets regardless of eye and head orientation (Blohm G, Lefèvre P. J Neurophysiol 104: 2103–2115, 2010), the brain must somehow take these signals into account. To learn about the neural mechanisms potentially underlying this visual-to-motor transformation, we trained a physiologically inspired neural network model to combine two-dimensional (2D) retinal motion signals with three-dimensional (3D) eye and head orientation and velocity signals to generate a spatially correct 3D pursuit command. We then simulated conditions of 1) head roll-induced ocular counterroll, 2) oblique gaze-induced retinal rotations, 3) eccentric gazes (invoking the half-angle rule), and 4) optokinetic nystagmus to investigate how units in the intermediate layers of the network accounted for different 3D constraints. Simultaneously, we simulated electrophysiological recordings (visual and motor tunings) and microstimulation experiments to quantify the reference frames of signals at each processing stage. We found a gradual retinal-to-intermediate-to-spatial feedforward transformation through the hidden layers. Our model is the first to describe the general 3D transformation for smooth pursuit mediated by eye- and head-dependent gain modulation. Based on several testable experimental predictions, our model provides a mechanism by which the brain could perform the 3D visuomotor transformation for smooth pursuit.

A Binocular Vision System for Underwater Target Detection

2013 ◽  
Vol 347-350 ◽  
pp. 883-890 ◽  
Author(s):  
Jie Shen ◽  
Hong Ye Sun ◽  
Hui Bin Wang ◽  
Zhe Chen ◽  
Yi Wei
Keyword(s):  
Binocular Vision ◽  
Stereo Matching ◽  
Vision System ◽  
Three Dimensional ◽  
Processing Unit ◽  
Dimensional Reconstruction ◽  
Underwater Target ◽  
Three Dimensional Coordinate ◽  
Target Detecting ◽  
Binocular Vision System

For the underwater target detecting task, a binocular vision system specialized to the underwater optical environment is proposed. The hardware platform is comprised of a image acquising unit, a image processing unit and a upper computer. Accordingly, the loaded software system is operated for the camera calibration, image preprocessing, feature point extraction, stereo matching and the three-dimensional restoration. The improved Harris operator is introduced for the three-dimensional reconstruction, considering the high scattering and strong attenuation by the underwater optical environment. The experiment results prove that the improved Harris operator is better adapt to the complex underwater optical environment and the whole system has the ability to obtain the three-dimensional coordinate of the underwater target more efficient and accurate.

Three-dimensional reconstruction of Shark Vertebrae: A technique with applications to age and growth studies

1992 ◽  
Vol 43 (5) ◽  
pp. 923 ◽  
Author(s):  
JG Clement ◽  
RA Officer ◽  
E Dykes
Keyword(s):  
Three Dimensional ◽  
Growth Patterns ◽  
Age And Growth ◽  
Initial Shape ◽  
Anatomical Structures ◽  
Vertebral Centra ◽  
Dimensional Reconstruction ◽  
Three Dimensional Coordinate ◽  
Realistic Images ◽  
Coordinate Data

Shark vertebral centra show no histological evidence of resorption at any time in the animals' life. Deorganification of centra always reveals a large, residual, stable, three-dimensional skeleton. In contrast, the mineralized parts of other organs (e.g. claspers and jaws) crumble into their individual mineralized subunits, the tesserae, upon deorganification. In both cases, only appositional growth of cartilage on the pre-existing mineralized template is possible. The basic 'double-cone' shape of the vertebrae facilitates increases in body length simultaneously with an accompanying increase in girth. Once the initial shape of the mineralized portion of a vertebral centrum is fully established and hence can be described, then relatively simple mathematical models might be devised to predict future growth patterns. To advance this hypothesis, it has first been necessary to develop a method that can accurately record the sizes and shapes of complex three-dimensional anatomical structures. This paper describes a technique that is capable not only of recording and measuring the size and shape of shark vertebrae but also of predicting their subsequent growth. Furthermore, the technique enables reproduction of three-dimensional coloured and shaded stereoscopic images of vertebral structures, facilitating a better understanding of their intricate morphology. Three-dimensional coordinate data gathered from any shark vertebra can be manipulated mathematically to model future vertebral growth. Producing realistic images of vertebrae transformed in this way may allow the exploration of possibly unrealized taxonomic affinities.

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