Field of view

The field of view (FOV) is the angular extent of the observable world that is seen at any given moment. In the case of optical instruments or sensors, it is a solid angle through which a detector is sensitive to electromagnetic radiation. It is further relevant in photography.

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Hey Vsauce Michael here. I am at the White House in America's capital Washington DC America makes alot of feature films every year Hollywood but they don't make the most feature films every year Nigeria makes more but the country that makes the most films every single year is India every two years the country of India fills up enough film with unique feature films that stretch all the way from this city, Mumbai, to where I live in London that's double what hollywood produces in two years that is a lot of movies but is real-life a movie? I've discussed the frame rate of the human eye before but how does the resolution of the human eye compare to a camera or screen? VHS, laserdisc, DVD Blu ray, IMAX. Numbers like these are pixel dimensions when multiplied they tell us the total number of picture elements an image is made up of a figure often used to describe digital cameras it might sound like more is better but to be sure numbers like 1920 by 1080 are not resolutions per say more pixels is only part of the equation. Resolution is about distinguishing fine details and that depends on a lot of other factors for instance the amount of light the sizeof the sensors what the millions of pixels are actually encoding and how close the subject is I mean up close Salvador Dali's painting of his wife looking at the Mediterranean can be resolved into boxes but from afar well it's Abraham Lincoln. for crying out loud on a small enough screen from far enough away low and high so-called resolutions on screens aren't even resolved differently from one another by your eye how different nearby pixels are from one another also matters this is called spatial resolution for instance if I go out-of-focus the number of pixels in the video frame stays the same but you can't resolve as much detail now with all this in mind we can still compare human vision to a digital image by asking a better question assuming everything else is optimal how many pixels would you need to make an image on a screen large enough to fill your entire field of view look like real life, without any detectable pixelation? Now we are getting somewhere kind of. The analogy is still cruddy because a camera snaps an entire frame at once whereas our eyes move around. The brain amalgamate their constant stream of information into what we call vision sight, in fact the image created by the eyeball alone during a single glance would hardly even be acceptable on a broken TV screen. We think our eyes create images like this picture Guy took of me with a camera but for one thing unlike a camera you've got some stuff in the way for instance you are always looking at your own nose and maybe even glasses if you have them. Luckily our brains process those stimuli out because they don't matter and they don't change but thinking those are the only difference is a pitfall, literally Latinly. The fovea gets its name from the Latin for pitfall, the fovea is the pit on your retina that receives light from the central two degrees of your field of view about the area covered by both your thumbs when held at arms length away. Optimal colour vision and 2020 acuity only possible within that little area when it comes to these limitations XKCD has a brilliant illustration it points out other problems like blind spots literal blank spaces in our vision where the optic nerve meets up with the retina and no visual information is received if you bought a camera that did this you would return it you can find your own blind spot by closing you're right eye fixating your left eye on a point in front of you extending your left thumb and then moving it left-of-center slightly slowly carefully until it's not there anymore crazy but of course we don't see the world horribly like this because our eyes are constantly moving dragging foveal resolution where ever we need it and our brains complex visual system fills in details merges images from both eyes and makes a lot of gueses what we can actually see is a processed image not computer-generated imagery but well meat generated imagery the neon color spreading illusion is a great way to demonstrate this difference there is no blue circle in this picture the white here is the same as the white here, a camera isn't fooled, a screen isn't fooled, only you and the fleeting gumbo of ingredients you call perception is fooled. Our vision is not analogous to a camera but our reformulated question can still be answered because human anatomy allows us to resolve to differentiate certain angular distances famously Roger N Clark used a figure of 0.59 arcminutes as the resolution of the human eye to calculate based on the size of our total field of view how many of these distinct elements could fit inside of it the result was an approximation of exactly what we want to know how many individual picture elements pixels our vision can appreciate his answer 576 megapixels that many pixels packed inside a screen large enough to fill your entire field of view regardless of proximity would be close enough to be undetectable by the average human eye. But we should factor in the fovea because Clarks calculation assumes optimal acuity everywhere, it allows the eye to move around but a single glance is more analogous to a camera snap and as it turns out only about seven megapixels packed into the two degrees of optimal acuity the fovea covers during a fixed stare are needed to be rendered undetectable it's been roughly estimated that the rest of your field of view would only need about 1 megapixel more information. Now that might sound low but keep in mind that there are plenty of modern technologies that already use pixel densities better than we can differentiate as bad astronomer deftly showed Apple's Retina Display's truly do contain pixels at a density average eyesight can't differentiate from typical reading distances but the fact that there are screen sizes and pixel densities that can fool the human eye is not a sign that we see in any kind of megapixelly way human vision just isn't that digital I mean sure like a camera sensor we only have a finite and discrete number of cells in our retina but the brain adjusts our initial sensations into a final perception that is a wishy-washy top-down processed blob of experience it's not made of pixels and furthermore unlike a camera it's not saved in memory with veracity like a digital camera file absolutely no evidence has ever been found for the existence of a truly photographic memory and what's even cooler is that not only do we not visually resolve the real world like a movie camera we also don't narratively resolve conflict and drama in our lives like most movie scripts. The point of all of this what I'm getting at is an idea an idea that initially drew me to this question we play roles in the movie of life but its a special kind of movie cinematic victories and struggles are often discrete resolved like pixels with unbelievably perfect beginnings and endings whereas the real world is all about ear resolution I like how Jack Angstreich put it in cinemania in a movie a character can make a decision and then walk away from the camera across the street and have the credits roll freezing life in a perfect happily ever after but in the real world after you cross the street you have to go home the world goes on life doesn't appear in any particular pixel resolution or narrative resolution things are continuous the world was running before you came around and it will continue running after you are gone your life is a plot only in so far as it begins and ends and occurs in medias res Damerish opens illustration for Charles McGrath's endings without ending says it perfectly in life they're rarely is the end, there is only the and and as always thanks for watching

Humans and animals

In the context of human and primate vision, the term "field of view" is typically only used in the sense of a restriction to what is visible by external apparatus, like when wearing spectacles^[2] or virtual reality goggles. Note that eye movements are allowed in the definition but do not change the field of view when understood this way.

If the analogy of the eye's retina working as a sensor is drawn upon, the corresponding concept in human (and much of animal vision) is the visual field.^[3] It is defined as "the number of degrees of visual angle during stable fixation of the eyes".^[4] Note that eye movements are excluded in the visual field's definition. Humans have a slightly over 210-degree forward-facing horizontal arc of their visual field (i.e. without eye movements),^[5]^[6] (with eye movements included it is slightly larger, as you can try for yourself by wiggling a finger on the side), while some birds have a complete or nearly complete 360-degree visual field. The vertical range of the visual field in humans is around 150 degrees.^[5]

The range of visual abilities is not uniform across the visual field, and by implication the FoV, and varies between species. For example, binocular vision, which is the basis for stereopsis and is important for depth perception, covers 114 degrees (horizontally) of the visual field in humans;^[7] the remaining peripheral 40 degrees on each side have no binocular vision (because only one eye can see those parts of the visual field). Some birds have a scant 10 to 20 degrees of binocular vision.

Similarly, color vision and the ability to perceive shape and motion vary across the visual field; in humans color vision and form perception are concentrated in the center of the visual field, while motion perception is only slightly reduced in the periphery and thus has a relative advantage there. The physiological basis for that is the much higher concentration of color-sensitive cone cells and color-sensitive parvocellular retinal ganglion cells in the fovea – the central region of the retina, together with a larger representation in the visual cortex – in comparison to the higher concentration of color-insensitive rod cells and motion-sensitive magnocellular retinal ganglion cells in the visual periphery, and smaller cortical representation. Since rod cells require considerably less light to be activated, the result of this distribution is further that peripheral vision is much more sensitive at night relative to foveal vision (sensitivity is highest at around 20 deg eccentricity).^[3]

Conversions

Many optical instruments, particularly binoculars or spotting scopes, are advertised with their field of view specified in one of two ways: angular field of view, and linear field of view. Angular field of view is typically specified in degrees, while linear field of view is a ratio of lengths. For example, binoculars with a 5.8 degree (angular) field of view might be advertised as having a (linear) field of view of 102 mm per meter. As long as the FOV is less than about 10 degrees or so, the following approximation formulas allow one to convert between linear and angular field of view. Let $A$ be the angular field of view in degrees. Let $M$ be the linear field of view in millimeters per meter. Then, using the small-angle approximation:

A\approx {360^{\circ } \over 2\pi }\cdot {M \over 1000}\approx 0.0573\times M

M\approx {2\pi \cdot 1000 \over 360^{\circ }}\cdot A\approx 17.45\times A

Machine vision

In machine vision the lens focal length and image sensor size sets up the fixed relationship between the field of view and the working distance. Field of view is the area of the inspection captured on the camera’s imager. The size of the field of view and the size of the camera’s imager directly affect the image resolution (one determining factor in accuracy). Working distance is the distance between the back of the lens and the target object.

Tomography

In tomography, the field of view is the area of each tomogram. In for example computed tomography, a volume of voxels can be created from such tomograms by merging multiple slices along the scan range.

Remote sensing

In remote sensing, the solid angle through which a detector element (a pixel sensor) is sensitive to electromagnetic radiation at any one time, is called instantaneous field of view or IFOV. A measure of the spatial resolution of a remote sensing imaging system, it is often expressed as dimensions of visible ground area, for some known sensor altitude.^[8]^[9] Single pixel IFOV is closely related to concept of resolved pixel size, ground resolved distance, ground sample distance and modulation transfer function.

Astronomy

In astronomy, the field of view is usually expressed as an angular area viewed by the instrument, in square degrees, or for higher magnification instruments, in square arc-minutes. For reference the Wide Field Channel on the Advanced Camera for Surveys on the Hubble Space Telescope has a field of view of 10 sq. arc-minutes, and the High Resolution Channel of the same instrument has a field of view of 0.15 sq. arc-minutes. Ground-based survey telescopes have much wider fields of view. The photographic plates used by the UK Schmidt Telescope had a field of view of 30 sq. degrees. The 1.8 m (71 in) Pan-STARRS telescope, with the most advanced digital camera to date has a field of view of 7 sq. degrees. In the near infra-red WFCAM on UKIRT has a field of view of 0.2 sq. degrees and the VISTA telescope has a field of view of 0.6 sq. degrees. Until recently digital cameras could only cover a small field of view compared to photographic plates, although they beat photographic plates in quantum efficiency, linearity and dynamic range, as well as being much easier to process.

Photography

In photography, the field of view is that part of the world that is visible through the camera at a particular position and orientation in space; objects outside the FOV when the picture is taken are not recorded in the photograph. It is most often expressed as the angular size of the view cone, as an angle of view. For a normal lens focused at infinity, the diagonal (or horizontal or vertical) field of view can be calculated as:

\mathrm {FOV} =2\times \arctan \left({\frac {\text{sensor size}}{2f}}\right)

where $f$ is the focal length, here the sensor size and $f$ are in the same unit of length, FOV is in radians.

Microscopy

In microscopy, the field of view in high power (usually a 400-fold magnification when referenced in scientific papers) is called a high-power field, and is used as a reference point for various classification schemes.

For an objective with magnification $m$ , the FOV is related to the Field Number (FN) by

\mathrm {FOV} ={\frac {\mathrm {FN} }{m}},

if other magnifying lenses are used in the system (in addition to the objective), the total $m$ for the projection is used.

Video games

The field of view in video games refers to the field of view of the camera looking at the game world, which is dependent on the scaling method used.

References

^ "Cascading Milky Way". ESO Picture of the Week. Retrieved 11 June 2012.
^ Alfano, P.L.; Michel, G.F. (1990). "Restricting the field of view: Perceptual and performance effects". Perceptual and Motor Skills. 70 (1): 35–45. doi:10.2466/pms.1990.70.1.35. PMID 2326136. S2CID 44599479.
^ ^a ^b Strasburger, Hans; Rentschler, Ingo; Jüttner, Martin (2011). "Peripheral vision and pattern recognition: a review". Journal of Vision. 11 (5): 1–82. doi:10.1167/11.5.13. PMID 22207654.
^ Strasburger, Hans; Pöppel, Ernst (2002). Visual Field. In G. Adelman & B.H. Smith (Eds): Encyclopedia of Neuroscience; 3rd edition, on CD-ROM. Elsevier Science B.V., Amsterdam, New York.
^ ^a ^b Traquair, Harry Moss (1938). An Introduction to Clinical Perimetry, Chpt. 1. London: Henry Kimpton. pp. 4–5.
^ Strasburger, Hans (2020). "Seven myths on crowding and peripheral vision". i-Perception. 11 (2): 1–45. doi:10.1177/2041669520913052. PMC 7238452. PMID 32489576.
^ Howard, Ian P.; Rogers, Brian J. (1995). Binocular vision and stereopsis. New York: Oxford University Press. p. 32. ISBN 0-19-508476-4. Retrieved 3 June 2014.
^ Oxford Reference. "Quick Reference: instantaneous field of view". Oxford University Press. Retrieved 13 December 2013.
^ Wynne, James B. Campbell, Randolph H. (2011). Introduction to remote sensing (5th ed.). New York: Guilford Press. p. 261. ISBN 978-1609181765.{{cite book}}: CS1 maint: multiple names: authors list (link)

This page was last edited on 5 February 2024, at 11:20

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