Speed discrimination and its relation to involuntary eye movements in human vision

1985 ◽  
Vol 54 (1) ◽  
pp. 7-12 ◽  
Author(s):  
John L. Barbur
Keyword(s):  
Eye Movements ◽  
Human Vision ◽  
Speed Discrimination

An Advanced Active Vision System with Multimodal Visual Odometry Perception for Humanoid Robots

2017 ◽  
Vol 14 (03) ◽  
pp. 1750006
Author(s):  
Xin Wang ◽  
Pieter Jonker
Keyword(s):  
Eye Movements ◽  
Vision System ◽  
Low Cost ◽  
Active Vision ◽  
Human Perception ◽  
Personal Space ◽  
Visual Odometry ◽  
Humanoid Robots ◽  
Industrial Applications ◽  
Human Vision

Using active vision to perceive surroundings instead of just passively receiving information, humans develop the ability to explore unknown environments. Humanoid robot active vision research has already half a century history. It covers comprehensive research areas and plenty of studies have been done. Nowadays, the new trend is to use a stereo setup or a Kinect with neck movements to realize active vision. However, human perception is a combination of eye and neck movements. This paper presents an advanced active vision system that works in a similar way as human vision. The main contributions are: a design of a set of controllers that mimic eye and neck movements, including saccade eye movements, pursuit eye movements, vestibulo-ocular reflex eye movements and vergence eye movements; an adaptive selection mechanism based on properties of objects to automatically choose an optimal tracking algorithm; a novel Multimodal Visual Odometry Perception method that combines stereopsis and convergence to enable robots to perform both precise action in action space and scene exploration in personal space. Experimental results prove the effectiveness and robustness of our system. Besides, the system works in real-time constraints with low-cost cameras and motors, providing an affordable solution for industrial applications.

Eye Movements and Practice Effects in the Attentional Dwell Time Paradigm

2013 ◽  
Vol 60 (1) ◽  
pp. 22-33
Author(s):  
Anders Petersen ◽  
Søren Kyllingsbæk
Keyword(s):  
Eye Movements ◽  
Dwell Time ◽  
Temporal Dynamics ◽  
Human Vision ◽  
Practice Effects ◽  
Time Interval ◽  
Direct Measure ◽  
Intensive Training ◽  
Spatial Locations ◽  
Attentional Dwell Time

In the attentional dwell time paradigm by Duncan, Ward, and Shapiro (1994) , two backward masked targets are presented at different spatial locations and separated by a varying time interval. Results show that report of the second target is severely impaired when the time interval is less than 500 ms which has been taken as a direct measure of attentional dwell time in human vision. However, we show that eye movements may have confounded the estimate of the dwell time and that the measure may not be robust as previously suggested. The latter is supported by evidence suggesting that intensive training strongly attenuates the dwell time because of habituation to the masks. Thus, this article points to eye movements and masking as two potential methodological pitfalls that should be considered when using the attentional dwell time paradigm to investigate the temporal dynamics of attention.

Eye Anatomy, Eye Movements and Vision

2012 ◽  
pp. 10-20 ◽  
Author(s):  
Fiona Mulvey
Keyword(s):  
Eye Movements ◽  
Human Computer Interaction ◽  
Eye Movement ◽  
Human Perception ◽  
Human Vision ◽  
Emotional States ◽  
Visual World ◽  
Potential Measurement ◽  
Movement Data ◽  
The Brain

This chapter introduces the basics of eye anatomy, eye movements and vision. It will explain the concepts behind human vision sufficiently for the reader to understand later chapters in the book on human perception and attention, and their relationship to (and potential measurement with) eye movements. We will first describe the path of light from the environment through the structures of the eye and on to the brain, as an introduction to the physiology of vision. We will then describe the image registered by the eye, and the types of movements the eye makes in order to perceive the environment as a cogent whole. This chapter explains how eye movements can be thought of as the interface between the visual world and the brain, and why eye movement data can be analysed not only in terms of the environment, or what is looked at, but also in terms of the brain, or subjective cognitive and emotional states. These two aspects broadly define the scope and applicability of eye movements technology in research and in human computer interaction in later sections of the book.

scholarly journals Closed loop motor-sensory dynamics in human vision

2019 ◽  
Author(s):  
Liron Gruber ◽  
Ehud Ahissar
Keyword(s):  
Eye Movements ◽  
Visual Processing ◽  
Closed Loop ◽  
Open Loop ◽  
Visual Input ◽  
Human Vision ◽  
Visual Inputs ◽  
Eye Motion ◽  
Slow Eye Movements ◽  
The Brain

AbstractVision is obtained with a continuous motion of the eyes. The kinematic analysis of eye motion, during any visual or ocular task, typically reveals two (kinematic) components: saccades, which quickly replace the visual content in the retinal fovea, and drifts, which slowly scan the image after each saccade. While the saccadic exchange of regions of interest (ROIs) is commonly considered to be included in motor-sensory closed-loops, it is commonly assumed that drifts function in an open-loop manner, that is, independent of the concurrent visual input. Accordingly, visual perception is assumed to be based on a sequence of open-loop processes, each initiated by a saccade-triggered retinal snapshot. Here we directly challenged this assumption by testing the dependency of drift kinematics on concurrent visual inputs using real-time gaze-contingent-display. Our results demonstrate a dependency of the trajectory on the concurrent visual input, convergence of speed to condition-specific values and maintenance of selected drift-related motor-sensory controlled variables, all strongly indicative of drifts being included in a closed-loop brain-world process, and thus suggesting that vision is inherently a closed-loop process.Author summaryOur eyes do not function like cameras; it has long been known that we are actively scanning our visual environment in order to see. Moreover, it is commonly accepted that our fast eye movements, saccades, are controlled by the brain and are affected by the sensory input. However, our slow eye movements, the ocular drifts, are often ignored when visual acquisition is analyzed. Accordingly, visual processing is typically assumed to be based on computations performed on saccade-triggered snapshots of the retinal state. Our work strongly challenges this model and provides significant evidence for an alternative model, a cybernetic one. We show that the dynamics of the ocular drifts do not allow, and cannot be explained by, open loop visual acquisition. Instead, our results suggest that visual acquisition is part of a closed-loop process, which dynamically and continuously links the brain to its environment.

scholarly journals Neural Representations of Faces are Tuned to Eye Movements

2018 ◽  
Author(s):  
Lisa Stacchi ◽  
Meike Ramon ◽  
Junpeng Lao ◽  
Roberto Caldara
Keyword(s):  
Face Recognition ◽  
Individual Differences ◽  
Eye Movements ◽  
Neural System ◽  
Human Vision ◽  
Facial Features ◽  
Sampling Strategies ◽  
Neural Representations ◽  
Facial Information ◽  
Visual Sampling

ABSTRACTEye movements provide a functional signature of how human vision is achieved. Many recent studies have reported idiosyncratic visual sampling strategies during face recognition. Whether these inter-individual differences are mirrored by idiosyncratic neural responses has not been investigated yet. Here, we tracked observers’ eye movements during face recognition; additionally, we obtained an objective index of neural face discrimination through EEG that was recorded while subjects fixated different facial information.Across all observers, we found that those facial features that were fixated longer during face recognition elicited stronger neural face discrimination responses. This relationship occurred independently of inter-individual differences in fixation biases. Our data show that eye movements play a functional role during face processing by providing the neural system with information that is diagnostic to a specific observer. The effective processing of face identity involves idiosyncratic, rather than universal representations.

scholarly journals Foveal vision predictively sensitizes to defining features of eye movement targets

2022 ◽  
Author(s):  
Lisa M Kroell ◽  
Martin Rolfs
Keyword(s):  
Eye Movements ◽  
Human Vision ◽  
Saccade Target ◽  
Large Field ◽  
Visual Features ◽  
Foveal Vision ◽  
Seamless Transition ◽  
Field Noise ◽  
The Impact ◽  
Passive Fixation

Despite the fovea's singular importance for active human vision, the impact of large eye movements on foveal processing remains elusive. Building on findings from passive fixation tasks, we hypothesized that during the preparation of rapid eye movements (saccades), foveal processing anticipates soon-to-be fixated visual features. Using a dynamic large-field noise paradigm, we indeed demonstrate that sensitivity for defining features of a saccade target is enhanced in the pre-saccadic center of gaze. Enhancement manifested in higher Hit Rates for foveal probes with target-congruent orientation, and a sensitization to incidental, target-like orientation information in foveally presented noise. Enhancement was spatially confined to the center of gaze and its immediate vicinity. We suggest a crucial contribution of foveal processing to trans-saccadic visual continuity which has previously been overlooked: Foveal processing of saccade targets commences before the movement is executed and thereby enables a seamless transition once the center of gaze reaches the target.

scholarly journals Humanoid Eyes: Perspective & Challenges

2019 ◽  
Author(s):  
Ahmad Yousef
Keyword(s):  
Prefrontal Cortex ◽  
Eye Movements ◽  
Brain Imaging ◽  
Saccadic Eye Movements ◽  
Essential Elements ◽  
Human Vision ◽  
Human Eye ◽  
Cortical Areas ◽  
The Continuum

This proposal offers perspective and challenges aiming to optimize and socialize the humanoid eyes. The main purpose of this proposal is to bring the readers’ attention to the importance and the sophistication of the human eye and its four dynamics continuum, namely, the continuum that may include saccadic eye movements, pupil variations, blinks along with duchenne markers. We suggested that the robotics’ designers to work collaboratively with neuroscientists to mathematically estimate the aforementioned continuum, and therefore, humanoid eyes/cameras can be perfectly invented; invention that we try to register its essential elements in the present study. The aforementioned collaboration will be very beneficial for an additional purpose, namely, because human vision indeed activates very many cortical areas that extended to the prefrontal cortex; the collaboration may effectively flourish the eye trackers to be good replacements of the expensive brain imaging in certain circumstances.

scholarly journals The analysis of the influence of fractal structure of stimuli on fractal dynamics in fixational eye movements and EEG signal

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Hamidreza Namazi ◽  
Vladimir V. Kulish ◽  
Amin Akrami
Keyword(s):  
Eye Movements ◽  
Visual Stimulus ◽  
Fractal Structure ◽  
Temporal Structure ◽  
Human Vision ◽  
Eeg Signal ◽  
Vision Disorders ◽  
Fixational Eye Movements ◽  
Electroencephalogram Eeg ◽  
The Brain

Abstract One of the major challenges in vision research is to analyze the effect of visual stimuli on human vision. However, no relationship has been yet discovered between the structure of the visual stimulus and the structure of fixational eye movements. This study reveals the plasticity of human fixational eye movements in relation to the ‘complex’ visual stimulus. We demonstrated that the fractal temporal structure of visual dynamics shifts towards the fractal dynamics of the visual stimulus (image). The results showed that images with higher complexity (higher fractality) cause fixational eye movements with lower fractality. Considering the brain, as the main part of nervous system that is engaged in eye movements, we analyzed the governed Electroencephalogram (EEG) signal during fixation. We have found out that there is a coupling between fractality of image, EEG and fixational eye movements. The capability observed in this research can be further investigated and applied for treatment of different vision disorders.

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