Concept

Visual field

The visual field is "that portion of space in which objects are visible at the same moment during steady fixation of the gaze in one direction"; in ophthalmology and neurology the emphasis is on the structure inside the visual field and it is then considered “the field of functional capacity obtained and recorded by means of perimetry”. However, the visual field can also be understood as a predominantly perceptual concept and its definition then becomes that of the "spatial array of visual sensations available to observation in introspectionist psychological experiments" (for example in van Doorn et al., 2013). The corresponding concept for optical instruments and s is the field of view (FOV). In humans and animals, the FOV refers to the area visible when eye movements – if possible for the species – are allowed. In optometry, ophthalmology, and neurology, a visual field test is used to determine whether the visual field is affected by diseases that cause local scotoma or a more extensive loss of vision or a reduction in sensitivity (increase in threshold). The normal (monocular) human visual field extends to approximately 60 degrees nasally (toward the nose, or inward) from the vertical meridian in each eye, to 107 degrees temporally (away from the nose, or outwards) from the vertical meridian, and approximately 70 degrees above and 80 below the horizontal meridian. The binocular visual field is the superimposition of the two monocular fields. In the binocular field, the area left of the vertical meridian is referred to as the left visual field (which is located temporally for the left, and nasally for the right eye); a corresponding definition holds for the right visual field. The four areas delimited by the vertical and horizontal meridian are referred to as upper/lower left/right quadrants. In the European Union, the minimum field requirement for driving is 50 degrees to either side of the vertical meridian and 120 degrees horizontally in total, and 20 degrees above and below the horizontal meridian.

Official source

https://en.wikipedia.org/wiki/Visual_field

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related courses (16)

AR-408: Drawing structures - Docta Manus

The Unit will introduce drawing as the key tool for communication between engineers and architects, and as a mediator between construction and the student. Through drawing, we will analyze selected structural projects that embody an exemplary interaction between space and structure.

ME-443: Hydroacoustic for hydropower plants

Introduction to pressure wave propagation phenomena in hydraulic circuits, water hammer calculations, transient behaviour of hydroelectric plants, 1D numerical simulation of the dynamic behaviour of Francis, Pelton and Kaplan turbines, and study of the sta ...

NX-421: Neural signals and signal processing

Understanding, processing, and analysis of signals and images obtained from the central and peripheral nervous system ...

Related lectures (32)

Visual Variables in Cartography

Covers visual variables in cartography, including interactions, laws of visual perception, and color coding.

Vision: systems & circuits

Explores receptive fields, visual brain areas, evolution-driven differences in visual pathways, and neural mechanisms underlying escape behavior.

Introduction into spatial maps and visual areas

Introduces spatial maps and visual areas in the cortex, including retinotopic organization and the Allen Reference Atlas.

Related publications (27)

Causal evidence for dorsal stream involvement in object shape recognition: A tractography-guided ccPAS study

Visual experience requires orchestration of intricate brain connections. One of the most influential models of human visual information processing posits two segregated streams and postulates that conscious object recognition relies exclusively on the ventral visual stream. However, recent evidence suggests that the dorsal stream is involved in encoding crucial attributes of visual object recognition, such as global shape. The specific role of the dorsal stream is controversial in this context. Through an i

MIT Press2026

Object recognition from sparse simulated phosphenes and curved segments

Cortical prostheses offer the potential for partial vision restoration in individuals with blindness by stimulating neurons to produce phosphenes. However, the low number of discrete phosphenes that can be simultaneously elicited in practice makes encoding of whole objects difficult, hindering recognition. Hence, we aim at determining the minimal number of discrete visual elements needed for object recognition. To answer this question, we replaced object contours by a varying number of round patches, servin

Elsevier BV2026

Durability of pultruded fibre-polymer composite structures under various environmental conditions over a period up to 25 years

Thomas Keller

The durability of two different types of structures and deck units composed of glass fibre-polymer composites exposed to various environmental conditions were investigated. The Pontresina Bridge and Eyecatcher Building were exposed to an alpine and urban climate for 25 years, respectively, and a pultruded deck unit was immersed in water for 8 years. The assessment included visual inspection of adhesively bonded and bolted joints, and fibre blooming, full-scale static loading, and investigations of coupons s

Elsevier BV2026

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Official source

https://en.wikipedia.org/wiki/Visual_field

About this result

Ontological neighbourhood

Health sciences

Ophthalmology: Topics in ophthalmology

Related courses (16)

AR-408: Drawing structures - Docta Manus

ME-443: Hydroacoustic for hydropower plants

NX-421: Neural signals and signal processing

Understanding, processing, and analysis of signals and images obtained from the central and peripheral nervous system ...

Related lectures (32)

Visual Variables in Cartography

Covers visual variables in cartography, including interactions, laws of visual perception, and color coding.

Vision: systems & circuits

Explores receptive fields, visual brain areas, evolution-driven differences in visual pathways, and neural mechanisms underlying escape behavior.

Introduction into spatial maps and visual areas

Introduces spatial maps and visual areas in the cortex, including retinotopic organization and the Allen Reference Atlas.

Related publications (27)

Causal evidence for dorsal stream involvement in object shape recognition: A tractography-guided ccPAS study

MIT Press2026

Object recognition from sparse simulated phosphenes and curved segments

Elsevier BV2026

Durability of pultruded fibre-polymer composite structures under various environmental conditions over a period up to 25 years

Thomas Keller

Elsevier BV2026

Related people (30)

Kevin Sivula

See webpage for more info limno.epfl.ch Teaching & PhD PhD Students Odile Louise Andres, Arthur Eliot Bouchez, Benjamin Goldman, Nicolas Johannes Diercks, Aurélie Fanny Marie Célérien, Jiajun Li, Louise Marie Foltzer-De Cian, Melanie Victoria Johanning, Nils William Laurent Golay Past EPFL PhD Students Andrea Gasperini, Pauline Bornoz, Xavier Adrian Jeanbourquin, Xiaoyun Yu, Mathieu Steven Prévot, Muhammad Aiman Bin Rahmanudin Hamdan, Nhât-Tân Vuong, Yongpeng Liu, Arvindh Sekar, Barbara Alexandra Primera

Touradj Ebrahimi

Touradj EBRAHIMI received his M.Sc. and Ph.D., both in Electrical Engineering, from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in 1989 and 1992 respectively. In 1993, he was a research engineer at the Corporate Research Laboratories of Sony Corporation in Tokyo, where he conducted research on advanced video compression techniques for storage applications. In 1994, he served as a research consultant at AT&T Bell Laboratories working on very low bitrate video coding. He is currently Professor at EPFL heading its Multimedia Signal Processing Group. He is also the Convenor of JPEG standardization Committee. He was also adjunct Professor with the Center of Quantifiable Quality of Service at Norwegian University of Science and Technology (NTNU)from 2008 to 2012. Prof. Ebrahimi has been the recipient of various distinctions and awards, such as the IEEE and Swiss national ASE award, the SNF-PROFILE grant for advanced researchers, Four ISO-Certificates for key contributions to MPEG-4 and JPEG 2000, and the best paper award of IEEE Trans. on Consumer Electronics . He became a Fellow of the international society for optical engineering (SPIE) in 2003. Prof. Ebrahimi has initiated more than two dozen National, European and International cooperation projects with leading companies and research institutes around the world. He is a co-founder of Genista SA, a high-tech start-up company in the field of multimedia quality metrics. In 2002, he founded Emitall SA, start-up active in the area of media security and surveillance. In 2005, he founded EMITALL Surveillance SA, a start-up active in the field of privacy and protection. He is or has been associate Editor with various IEEE, SPIE, and EURASIP journals, such as IEEE Signal Processing Magazine, IEEE Trans. on Image Processing, IEEE Trans. on Multimedia, EURASIP Image Communication Journal, EURASIP Journal of Applied Signal Processing, SPIE Optical Engineering Magazine. Prof. Ebrahimi is a member of Scientific Advisory Board of various start-up and established companies in the general field of Information Technology. He has served as Scientific Expert and Evaluator for Research Funding Agencies such as those of European Commission, The Greek Ministry of Development, The Austrian National Foundation for Scientific Research, The Portuguese Science Foundation, as well as a number of Venture Capital Companies active in the field of Information Technologies and Communication Systems. His research interests include still, moving, and 3D image processing and coding, visual information security (rights protection, watermarking, authentication, data integrity, steganography), new media, and human computer interfaces (smart vision, brain computer interface). He is the author or the co-author of more than 200 research publications, and holds 14 patents. Prof. Ebrahimi is a member of IEEE, SPIE, ACM and IS&T. See the URL below for more details: http://mmspl.epfl.ch

Jean-Marc Odobez

Expertise Computer Vision, machine Learning (Bayesian models, deep learning), multimodal processing.Activity analysis, human behavior understanding, human communication, interaction modeling Dr Jean-Marc Odobez (Msc 1990, PhD 1994) received his Ph.D degree from Rennes University in 1994 for his PhD dissertation done at INRIA. After 5 years as an assistant professor at the University du Maine, France, he decided to join Idiap, where he is now the Head of the Perception & Activity Understanding Group and adju

Pascal Frossard

Teaching & PhD PhD Students Yiming Qin, Alba Carballo Castro, Elisa Messori, Ke Wang, Sevda Ögüt, Tuna Alikasifoglu, William Cappelletti, Manuel Madeira, Mahdi Amiri, Ortal Yona Senouf, Vasiliki Rizou, Cem Bilaloglu, Abdellah Rahmani, Amel Abdelraheem, Jérémy Jean Philippe Baffou, Adam Hazimeh, Vincent Jung, Yike Zhao Past EPFL PhD Students Dan Jurca, Jean-Paul Wagner, Ivana Radulovic, Ivana Tosic, Effrosyni Kokiopoulou, Zafer Arican, Vijayaraghavan Thirumalai, Tamara Tosic, Eirina Bourtsoulatze, Elif Vur

Roger Hersch

Roger D. Hersch is professor of Computer Science and head of the Peripheral Systems Laboratory at EPFL. He received his engineering degree from ETHZ in 1975, worked in industry from 1975 to 1980, and obtained his PhD degree from EPFL in 1985. He directed the widely known Visible Human Web Server project , which offers a number of services for the visualization of human anatomy. His current research focuses on color reproduction, spectral color prediction models, moiré imaging, and visual document security. Recent achievements include the PhotoProtect technology, which incorporates text as chromatic differences in order to protect identity photographs (Swiss driving license), microstructure imaging, which is used by railways companies (SNCF, RENFE) and festival organizers (Paleo) to print tickets at home and the band moire imaging technology for the protection of security documents.

Dario Floreano

Prof. Dario Floreano is director of the Laboratory of Intelligent Systems at the Swiss Federal Institute of Technology Lausanne (EPFL). Since 2010, he is the founding director of the Swiss National Center of Competence in Robotics, a research program that brings together more than 20 labs across Switzerland. Prof. Floreano holds an M.A. in Vision, an M.S. in Neural Computation, and a PhD in Robotics. He has held research positions at Sony Computer Science Laboratory, at Caltech/JPL, and at Harvard University. His main research interests are Robotics and A.I. at the convergence of biology and engineering. Prof. Floreano made pioneering contributions to the fields of evolutionary robotics, aerial robotics, and soft robotics. He served in numerous advisory boards and committees, including the Future and Emerging Technologies division of the European Commission, the World Economic Forum Agenda Council, the International Society of Artificial Life, the International Neural Network Society, and in the editorial committee of several scientific journals. In addition, he helped spinning off two drone companies (senseFly.com and Flyability.com) and a non-for-profit portal on robotics and A.I. (RoboHub.org). Books Manuale sulle Reti Neurali, il Mulino (in Italian), 1996 (first edition), 2006 (second edition)Evolutionary Robotics, MIT Press, 2000 Bio-Inspired Artificial Intelligence, MIT Press, 2008 Flying Insects and Robots, Springer Verlag, 2010

Thomas Ka Chung Lam

Aude Billard

Expertise RoboticsMachine LearningArtificial IntelligenceHuman-Robot InteractionMechatronicsDynamical Systems ControlComputational Neuroscience Aude Billard is full professor and head of the LASA laboratory at the School of Engineering at the Swiss Institute of Technology Lausanne (EPFL), and the Director of the Swiss Innovation Booster on Robotics. Dr. Billard acts as the President of the IEEE Robotics and Automation Society (RAS), after serving in several roles in the administrative and executive committe

Olivier Verscheure

SWISS DATA SCIENCE CENTER Housed at both EPFL and ETH Zurich, the newly created Swiss Data Science Center (SDSC) will address the fragmentation within today's data and analytics landscapes. The SDSC will be composed of a distributed multi-disciplinary team of data scientists and experts in domains including personalized health and personalized medicine, transportation, earth and environmental science, social science and digital humanities, and economics. The center aims to federate data providers, data and

Eleonora Borda

Related units (12)

Foundation Bertarelli Chair in Cognitive Neuroprosthetics

Laboratory of Integrated Performance in Design

L'IDIAP Laboratory

Related startups (1)

Visual Structure

AI & Robust Algorithms Empowering Option Traders

Related concepts (26)

Human eye

The human eye is a sensory organ, part of the sensory nervous system, that reacts to visible light and allows humans to use visual information for various purposes including seeing things, keeping balance, and maintaining circadian rhythm. The eye can be considered as a living optical device. It is approximately spherical in shape, with its outer layers, such as the outermost, white part of the eye (the sclera) and one of its inner layers (the pigmented choroid) keeping the eye essentially light tight except on the eye's optic axis.

Peripheral vision

Peripheral vision, or indirect vision, is vision as it occurs outside the point of fixation, i.e. away from the center of gaze or, when viewed at large angles, in (or out of) the "corner of one's eye". The vast majority of the area in the visual field is included in the notion of peripheral vision. "Far peripheral" vision refers to the area at the edges of the visual field, "mid-peripheral" vision refers to medium eccentricities, and "near-peripheral", sometimes referred to as "para-central" vision, exists adjacent to the center of gaze.

Tunnel vision

Tunnel vision is the loss of peripheral vision with retention of central vision, resulting in a constricted circular tunnel-like field of vision. Tunnel vision can be caused by: Eyeglass users experience tunnel vision to varying degrees due to the corrective lens only providing a small area of proper focus, with the rest of the field of view beyond the lenses being unfocused and blurry. Where a naturally sighted person only needs to move their eyes to see an object far to the side or far down, the eyeglass wearer may need to move their whole head to point the eyeglasses towards the target object.

Related exercises (7)

Mass hanging on a circuit

A mass m, subject to gravity, is hanging on a rectangular circuit in which circulates a current I. The superior part of the circuit is located inside of an uniform magnetic field B₀ perpendicular to the plane of the figure. Determine B₀ such that the mass freely floats. When we increase the current, we notice that the circuit and the mass are moving upwards. What is the work realised by the magnetic field when the mass goes upwars with Δzu2004=u2004h? The field applies on the horizontal side a force ${\bf

Rectangular coil

A coil, made of N rectangular turns of length l and of width w, has a resistance R. The coil, which is moving with a constant velocity

{\bf u} = u\,{\bf \hat{x}}

, enters a region subject to a uniform magnetic field

{\bf B}=-B_0\,{\bf \hat{z}}

. We will neglect the self-inductance of the circuit. Calculate the amplitude and direction of the induced current when : the coil is partially inside the region subject to the field B; the coil is entirely in this region ; the coil starts to go out of the regi

Vortex of Rankine

The vortex of Rankine is a model of a fluid defined by the velocity field (Ω=const):

{\bf v} = \Omega \,r \,{\bf\hat{\phi}} \quad r\leq a~; \qquad {\bf v} = \frac{\Omega\, a^2}{r} \,{\bf\hat{\phi}} \quad r> a~.

The flow is stationary, the fluid uncompressible, and we will neglect gravity. Determine the vorticity

({\bf T}=\nabla \times {\bf v})

of the flow as well as the pressure field P(r) with the condition P(r→∞)u2004=u2004P_(∞). Suggestion: use the vectorial identity: $({\bf v}\cdot \nabla){\bf v

Related people (30)

Related exercises (7)

Mass hanging on a circuit

Rectangular coil

A coil, made of N rectangular turns of length l and of width w, has a resistance R. The coil, which is moving with a constant velocity

{\bf u} = u\,{\bf \hat{x}}

, enters a region subject to a uniform magnetic field

{\bf B}=-B_0\,{\bf \hat{z}}

Vortex of Rankine

The vortex of Rankine is a model of a fluid defined by the velocity field (Ω=const):

{\bf v} = \Omega \,r \,{\bf\hat{\phi}} \quad r\leq a~; \qquad {\bf v} = \frac{\Omega\, a^2}{r} \,{\bf\hat{\phi}} \quad r> a~.

The flow is stationary, the fluid uncompressible, and we will neglect gravity. Determine the vorticity

({\bf T}=\nabla \times {\bf v})

of the flow as well as the pressure field P(r) with the condition P(r→∞)u2004=u2004P_(∞). Suggestion: use the vectorial identity: $({\bf v}\cdot \nabla){\bf v