filmmaking education and training
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Be a better key grip with Mark Vargo's short documentary about grips

Be a better key grip with Mark Vargo's short documentary about grips | filmmaking education and training |
Mark Vargo's Short documentaty 'Grip it Good' gives us a glimpse inside the world of working as a grip on major motion pictures.
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The Social Network - Designing Dialogue

This is a reupload from my secondary channel now that my copyright strike has expired. Original upload date: June 14th 2016 Support this Channel on Patreon
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Using Beards as Bounce Cards (& Other Cool Lighting Tricks Used in 'The Hateful Eight')

Using Beards as Bounce Cards (& Other Cool Lighting Tricks Used in 'The Hateful Eight') | filmmaking education and training |
You can tell right away when you're watching a Quentin Tarantino film.
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Kansas, Can Do: Why You Can Sustain an Independent Moviemaking Career Outside of L.A., NYC and Austin - MovieMaker Magazine

Kansas, Can Do: Why You Can Sustain an Independent Moviemaking Career Outside of L.A., NYC and Austin - MovieMaker Magazine | filmmaking education and training |
You don’t need to live in L.A., New York, Austin—or anywhere deemed "acceptable"—in order to be a successful filmmaker, says this Kansas director.
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5 Tips for Growing Your Filmmaking Career | Online Film Education

5 Tips for Growing Your Filmmaking Career | Online Film Education | filmmaking education and training |
No matter what you’re trying to be in your career, there is one thing that never changes and stays true - the relationships you build.
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Akira Kurosawa - Composing Movement

Can movement tell a story? Sure, if you’re as gifted as Akira Kurosawa. More than any other filmmaker, he had an innate understanding of movement and how t
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$15 DIY Film Rain Machine

More info: Lighting Dozen Tutorials: Exclusive film tutorials:
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Stanley Kubrick - The Cinematic Experience

An artist whose work could not be confined by genre or technique. We know so much about Stanley Kubrick and yet he remains an enigma of the art form. Press t...
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11 Thoughts: An Introduction to Photographic Composition

11 Thoughts: An Introduction to Photographic Composition | filmmaking education and training |
Composition noun com·po·si·tion \ˌkäm-pə-ˈzi-shən\ : the way in which something is put together or arranged : the combination of parts or elements that make up something
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Understanding Hyperfocal Distance (Podcast 437) • Martin Bailey Photography

Today I explain hyperfocal distance, and how using this distance can help you to achieve pan focus in your images when necessary.
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Here's Every Type of LEE Diffusion Explained

Here's Every Type of LEE Diffusion Explained | filmmaking education and training |
This video helps demonstrate the subtle differences in LEE diffusion materials.
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5 Skills That Will Make You a More Valuable Filmmaker

More reviews and tutorials at There are tons of skills that will make you a better filmmaker, but here are 5 skills that I like ...
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BLOG: Filmmakers - 7 Rules To Succeed in the Film Business

BLOG: Filmmakers - 7 Rules To Succeed in the Film Business | filmmaking education and training |
Filmmakers - 7 Rules To Succeed in the Film Business - blog post by Brendan Foley. Tags: Guest Post, Acting, Filmmaking, Producing, Advice. I love this...
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Seven Samurai - Drama Through Action

Support this Channel on Patreon: Follow me on Twitter: Follow me on Instagram
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A Massive List of Fall 2016 Grants All Filmmakers Should Know About

A Massive List of Fall 2016 Grants All Filmmakers Should Know About | filmmaking education and training |
A new season of grant deadlines are in, and now is the time to start applying!
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31 Must-Read Screenwriting Lessons From The Twilight Zone Creator Rod Serling - ScreenCraft

31 Must-Read Screenwriting Lessons From The Twilight Zone Creator Rod Serling - ScreenCraft | filmmaking education and training |
ScreenCraft's Ken Miyamoto showcases The Twilight Zone creator Rod Serling's best quotes on writing and elaborates on the lessons to be learned.
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28mm Lenses: The Secret Ingredient For Achieving A Film Look

28mm Lenses: The Secret Ingredient For Achieving A Film Look | filmmaking education and training |
For those of you that follow this blog regularly, you know that achieving a filmic look when shooting digitally is very important to me and something I often
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How to Perform a Camera Test: Narrow Your Focus to Three Simple Things - MovieMaker Magazine

How to Perform a Camera Test: Narrow Your Focus to Three Simple Things - MovieMaker Magazine | filmmaking education and training |
When shooting a project on film, camera tests were a given. They were not something a DP would even have to request. Camera tests were budgeted and scheduled into the preparation period of a movie, even if a DP knew a film stock like the back of their hand. Why bother test them again and again?
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Colour In Storytelling

or "Why is my Lightsaber Blue?" Press CC to see a list of the movies shown. TRACKLIST: 0:00-3:10 Aphex Twin - Avril 14th 3:15-8:49 Childish Gambino - Flight ...
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Composition In Storytelling

The cinema screen is just another canvas for an artist to create images. Composition is the tool that gives those images structure and purpose. Press the CC ...
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Raw is Not Magic

Raw is Not Magic | filmmaking education and training |
When you open an image from your digital SLR (or Cinema DNG files from
something like the Blackmagic Cinema Camera or Digital Bolex) in something
like Adobe's Lightroom, and reduce the exposure to reveal a huge amount of
information in the highlights — or radically adjust the white balance to
recover a well-balanced image from a murky orange mess, it's easy to feel
that the raw files are somehow more than just pixels. It almost feels

This sense of raw images being a true digital negative — deep, rich,
forgiving of exposure errors, and massively tunable to your ultimate taste,
leads some to feel that raw is always a better choice than the other common
way of capturing a high-dynamic range cinema image: log.

“Log” is a broad term to describe images images stored with logarithmic
(rather than linear or gamma-encoded) pixel values. You don’t see this
format available often in still cameras (GoPro is a notable exception), but
it’s commonplace in higher-end video cameras. The intent of log is similar
to the intent of raw — to capture and preserve as much dynamic range as
possible. Like raw, log images require post-processing to “look right.”

Are your familiar with shooting flat? Log is the ultimate flat.

A Typical Scene

Shut up, it's totally typical. And this is roughly how your eye might see


The same scene as captured by a still camera in raw, and processed at the
default settings by photo software. Note that the image has a pleasing
contrast, but the sky is blown-out.


The linear pixel values stored in the raw file. Note that the sky isn't as
blown-out as it looked, meaning we can recover it later in software.


The same scene stored in log pixel values. The image appears "flat," but
the log pixels have the same overexposure latitude in the sky as the raw
ones do.

Cameras that shoot raw are great. But so are cameras that shoot log. A
properly-recorded log image can be as powerful and flexible as a raw one,
and can even have some advantages over raw.

And raw? It’s not magic — but the reasons it can feel that way are worth

The Double-Edged Sword of Linear Light

Raw images are typically stored in linear-light values. A reasonable
definition of raw is “what the sensor captured,” and the sensor records
light in light’s own measure, meaning that +1 stop = twice as much light =
2x the numerical value in a digital file.

Linear Exposure Values

This logical arrangement turns out to be inefficient as heck in any kind of
quantized digital file. Half of your available tonal range is dedicated to
the single brightest stop of your image, so raw files have to have very
high bits depths to hold detail in the low exposure areas. It’s not unusual
for raw files to be 12- or 14-bit. But it’s not useful to directly compare
those numbers against the bit depths of log or video encoded files, where
the tonal range is distributed non-linearly.

The huge advantage of storing raw files in linear-light is that no
conversion has been baked-in to make them “look nice” on a non-linear
display. No subjective corrections, such as contrast curves or color
adjustments have been applied. This (among many other factors) means that a
raw file is not inherently ready to be viewed. It must be interpreted by
software and converted to a viewable state. And this interpretation process
is inherently subjective — even if you, the shooter, don't get involved.

“Straight Out of the Camera” Raw is a Myth

This is a little pet peeve of mine. You’ll sometimes see photo dorks post
photos from a new camera with the intention of showing “what the camera can
do,” so they make a point of noting that the image has “no processing” or
is “straight out of the camera”. This is only a valid notion for JPEG or
other baked-in-processing formats. In the case of raw files, what they
really should be saying is that they’re showing you the default processing
of whatever raw conversion software they’re using — which is going to be
different in Lightroom than it will be in Apple Photos or Capture One. If
you don’t touch the controls in your raw software, the image is not
“unprocessed.” It’s just processed according to the subjective decisions of
a team of software engineers instead of you.

Often those engineers have labored to make their default processing match
our expectations, by visually matching the JPEG previews we saw on the
camera’s LCD screen. In Lightroom, for example, this is made possible by
carefully-crafted camera “profiles,” which are essentially sets of
invisible sliders adjusted to pre-process the shot into an expected
appearance, while leaving the visible controls at their defaults. In these
cases, the hard work of the developers actually perpetuates the myth that
there’s something “pure” or untouched about a raw file left at its default
processing settings. The truth is, any raw processing is subjective, and
plays a major role in the appearance of a photo or motion picture frame.

Log is as Good as Linear, Maybe Better

Where a linear-light image is stored such that the numerical values
directly equate with light intensities, log images are arranged so that the
same number of pixel values are used for every stop in the image.

An idealized 0.0–1.0 linear image uses values 0.5–1.0 for the brightest
stop, 0.25–0.5 for the second-brightest, 0.125–0.5 for the third brightest,
0.0625–0.125 for the fourth brightest, and so on. At the fourth-brightest
stop, we're already down to the bottom 6% of the available pixel values.
The middle-range of your image, your exposure sweet-spot, is stored
entirely in the bottom 3% of the available data range.

Pixel Values per Stop in Linear and Log

Log, on the other hand, uses its pixel values much more efficiently. If a
log image holds ten stops, then 0.0–0.1 is used for the darkest stop,
0.1–0.2 is for stop 2, 0.2–0.3 is for stop 3, and so on, up to 0.9–1.0 for
stop 10. Each stop gets exactly the same amount of data fidelity.

See what I mean about log being the flattest of the flat picture “styles"
or “profiles”? When I created Prolost Flat, I was aiming for something as
close to log as I could get.

In both log and linear images, color adjustments can easily be natural and
organic, because the number spaces so easily invite simple math to relate
directly to light values.

* In a linear image, adjust exposure with multiplication. To brighten
an image by one stop, multiply the values by 2. To darken an image by
two stops, multiply the values by 0.25.
* In a log image, exposure is adjusted with addition/subtraction, which
is sometimes called offset. To brighten an image by one stop, add one
stop’s worth of values to the image. In our 10-stop example, that
would be 0.1. So adding 0.1 the the pixel values bumps exposure up
one stop. To reduce exposure by two stops, subtract 0.2.

When someone points out that raw images are eminently color-correctable,
it’s worth remembering that the same is equally true of log. And since log
images better utilize their data range, they don’t require as high a
bit-depth to hold a high-fidelity image. A hypothetical 10-bit linear raw
image has substantially less color fidelity where it counts than an
all-other-factors-being-equal 10-bit log image.

Raw Pixels are Rapidly Reduced to Regular Pixels

One myth of raw processing is that it happens all at once. This is not
true. Every raw processing engine has an order of operations. And very
early on in that order of operations is the debayering step, where the
monochrome, color-filtered pixels are cleverly interpolated into unique RGB
values per pixel.

After this operation is performed, the result is a set of very nice,
high-bit-depth, linear-light RGB pixels. These pixels are no different than
any other very nice RGB pixels. In fact, they’re somewhat challenged, since
the debayering process isn’t perfect, so the RGB values may have aliasing
and other undersampling artifacts.

All of the subsequent image processing in your raw software is done to
these regular, non-magic, RGB pixels.

Some raw adjustments, like sharpening and other detail tweaks, may dig all
the way back to the demosaicing stage in the pipeline. But that doesn't
change the fact that the first step in the image processing pipeline is to
make good, old-fashioned RGB pixels out of the raw file.

What this means is that the vast majority of the “raw image processing” to
which we ascribe so many magical powers, is just good, old fashioned RGB
image processing — that could just as easily be done to, say, a TIFF file,
or a 10-bit log ProRes frame, as it could to a raw image.

Myth: Raw Images Have No Native White Balance

One of the “magic” properties of a raw image is that it is said to have no
inherent white balance. You get to “white balance after the fact.” This is
one of the easiest demos of why raw is so great. It’s quite easy, for
example, to shoot a daylight-balanced JPEG in tungsten lighting and
demonstrate how nearly impossible it is to correct it to a properly
white-balanced image. Capture the same shot raw, and the process is

But the reason this works is not that the raw image has no inherent, or
native white balance. It does. The RGB color filters let in certain
wavelengths of light, and these are chosen carefully by the manufacturer to
result in a robust, but specific, colorimetry. There’s one and only one
color of light that pings the reg, green, and blue-filtered pixels to the
same value, and that’s the native color temperature of a bayer-pattern

The reasons its hard to rescue a poorly-white-balanced 8-bit JPEG are
numerous, and they compound on one another. An image shot at the wrong
white balance will inevitably be very dark in one of the color channels —
for example, our tungsten-lit, daylight-balanced JPEG will be so orange in
appearance that the blue channel might be near-black. Fixing the image
means brightening up the blue channel so much that we're going to not only
experience nasty quantization from bringing up the deep shadows of the
8-bit image, but compression artifacts as well. Compression is perceptual,
so when the compression engine sees a really dark blue channel, it assigns
it very little of the available data values.

This is made much worse by the subjective tone and color adjustments that
are baked into that JPEG. A pleasing contrast curve (or s-curve) makes a
well-balanced JPEG look lovely. But part of how it does that is to create a
"toe," or an area in the extreme shadows where values gradually taper off
to pure black. Values in this range are quite similar, i.e. difficult to
distinguish visually, and are therefore likely to be compressed heavily.
When you brighten up that blue channel, you're trying to make useful,
visible pixels out of this intentionally-mushed-down and
mercilessly-compressed portion of the image.

Contrast curves and compression happen very late in the raw processing
pipeline, but white balance happens quite early. The problem with trying to
correct an improperly white balanced JPEG could be categorized as a
colossal error in order of operations. So rescuing a poorly-white-balanced
JPEG involves revealing the very worst of an image that was designed to be
seen, but not touched.

When you adjust the white balance of a raw image, you're acting on the
linear-light RGB pixels that resulted from the debayer phase. White balance
is actually a very simple operation — it's nothing more than exposure
adjustments in R, G and B. You’re doing this under a bunch of the other
processing that goes into making a JPEG look nice, such as the s-curve and
color adjustments.

So white balance is just exposure. Remember how easy exposure adjustments
are in linear light? Remember also how easy they are in log?

A good log image is just as re-white-balanceable as a raw one.

I Don’t Believe You. It’s Frickin’ Magic

Not magic. But there is some really clever stuff going on in most raw
processing software that can make it seem like raw images have magical

Remember that white balance is just exposure adjustments per channel. For
example, to warm up an image using white balance controls, you're
increasing red exposure a lot, green a little, and decreasing blue.

When decreasing exposure, you can run into issues with highlights. A
blown-out highlight, reduced in exposure, is not pretty.

An easy way to show off the power of raw is to use your raw processing
software to reduce the exposure of a seemingly blown-out image. Often
you'll see highlight detail appear as if by magic. Of course, it's not
magic at all — it was there all along, but held in reserve. The reason for
this is actually less about giving you room to reduce overall exposure in
post, but rather for white balancing.

Reducing exposure on this raw file in Lightroom reveals a blue sky where
the default settings were clipped to white.

Holding some overexposure in reserve means that when you adjust white
balance, which entails reducing exposure in at least one of the RGB
channels, you can bring in new, valid highlight detail in those channels.
You can sense this happening as you adjust white balance in Lightroom — it
doesn't feel like color correcting — It feels like something “more.” But
it’s just well-designed software with a proper order of operations (the
last step of which is a pleasing s-curve), working from a robust digital
negative, that allows a simple thing like white balancing to reveal
previously-hidden image information.

But this comes at a cost. Remember that the top two stops of your image
take up 3/4 of your available pixel values. If your raw image holds three
stops of overexposure in reserve, that means that the visible portion of
your image is restricted to 1/8 of your pixel values. In a 12-bit image,
which can hold 4,096 shades of gray, this means that the visible portion of
your image only gets 512 values. That’s only twice as many as in an 8-bit

Reducing the exposure on this Alexa Log C frame in Nuke, viewing under an
sRGB preview LUT, reveals the previously blown-out detail in the sky.
Screen capture courtesy of Dan Sturm.

I Still Don't Believe You. Magic.

Some raw software will allow you to do extreme exposure reductions, past
the point where the camera data is capable of producing usable highlight
imagery on its own. Everybody clips, including raw-shooting cameras. And
since cameras have native white balances, inevitably one channel is going
to blow out before the other two.

Most raw software includes clever algorithms for recovering highlights that
are blown out in one or two channels. The rebuild highlight detail missing
from one channel by borrowing from the other two. Sometimes this results in
apparent miracles. Other times, the recovered highlights appear ashen and
monochromatic. This is one aspect of the raw processing that Adobe has
improved massively over time. Recovered highlights that appeared gray in
Adobe Camera Raw “Processing Version 2010” (used in Lightroom prior to
version 4) can have natural-looking color in PV2012 (Lightroom 4.0 and up).

So no, not magic. But maybe close enough.

Advantages of Raw over Log
* Demosaicing is done in software, and can be tuned per-image in post
(although almost no one bothers).
* Raw software often has sophisticated highlight recovery techniques
* Raw software is usually metadata-aware, and can therefore tune its
processing to the specifics of the camera.
* Raw files are no bigger than they need to be
* Since you never see the whole dynamic range flattened into a single
RGB image, you’re not likley to help popularize a terrible “flat
look” trend.
Advantages of Log over Raw
* Better color fidelity at lower bit-depths — you don’t need a
crazy-high bit-depth to preserve detail in shadows
* No special software required to view/edit
* Provides a common reference RGB for all of post production (on-set
LUT preview, editorial, VFX)
* Does not encourage magical thinking
* Unlike raw files, log files generally do not provide enough rope with
which to hang oneself
So When Should I Shoot Raw?

Raw may not be “magic,” but it is often a very smart choice.

I shoot raw for all my still photos, because my photo-processing software
is optimized for it. Even if Lightroom could correctly interpret and
process log stills, there’d be no point in shooting log stills, because
they’d by necessity be a processed subset of the camera’s capture. A nice
thing about raw is that it is (more or less) what the sensor captured. And
raw files are no bigger than they have to be, since they are usually
monochromatic. An 14-bit uncompressed raw still from my a7SII is about 24
MB. The same image, at the same quality, would be about 48 MB as a 10-bit
log DPX file.

While you can build a pipeline that enables color adjustments as powerful
and organic as Lightroom’s for your log imagery, few people actually do
this (the log grading presets in Magic Bullet Looks 3 are a great place to
start if you’re interested). But Lightroom-style processing for raw is as
simple as, well, using Lightroom — or any of the many other raw processing
tools available.

Raw files are storage efficient and allow you to defer processing decisions
until after the shoot. For stills, they’re a no brainer. And for folks
comfortable with the workflow, digital cinema raw such as that from RED can
enabled some very exciting workflows. Since RED’s raw files are compressed,
their data rate is low enough that you can edit them un-transcoded in many
NLEs, and get realtime playback even with 5K and up material.

Not magic — but maybe close enough.

However, that luxury comes at the cost of deferred processing. Someone has
to make the pixels someday. After all that real-time 5K editing, you have
to render — a process that can make you think of the term “progress bar” as
a cruel joke.

Not all raw files are so bandwidth friendly though. Cameras like Blackmagic
Design’s various offerings and the Digital Bolex, among many others, shoot
to losslessly-compressed DNG, an open raw standard crated by Adobe. DNG
sequences may or may not be supported by your NLE, and if they are, you’ll
need some major throughput to work with them in real time.

Log Looks Great and Is Often Prudent

With log files, you can often be bringing back just as much exposure
information as raw, but in a format that’s far less likely to cause

There are caveats, of course. As with raw, not all log is created equal.
There’s a big difference between compressed 8-bit s-log3 from my a7S II and
10-bit logC from an Arri Alexa.

One tremendous advantage of capturing log is that you are bringing RGB
pixels to an RGB pixel party. No transcoding is required to work with your
footage anywhere and everywhere. You can apply LUTs on set and expect those
LUTs to do exactly the same thing in post. You can provide camera originals
to your VFX team and expect them to hand back matching files that will cut
right into your DI without any fuss.

With raw, you’re far less likely to make a crucial mistake with setting up
your camera that results in a catastrophic exposure mistake. These days are
mostly over, but it was only a few years ago that I shot a commercial for
an agency that had a no-RED policy after a day’s worth of footage was
ruined by underexposure. What they’d seen through the viewfinder and tap
had looked fine, because the camera’s ISO was cranked up. In RED raw, ISO
is just metadata, so their footage was actually horribly underexposed.

Log, in its many flavors, is a smart, flexible, and powerful way of storing
high dynamic range digital cinema imagery. It’s closer to raw than you
might think, and often much easier to work with for results of the same or
better quality.


I started writing this post in July of 2013, but laziness got the best of
me. Since then Squarespace added these cool live charts, so it got a lot
easier to bore you with numbers visually. Thanks to Paul Schneider for the
tweet that got me to dust this one off and post it, to world-famous
colorist and gentleman Dave Hussey for corroborating it, to Dan Sturm for
the Nuke screen capture, and to all the folks on Twitter who expressed
interest in reading more nerdy stuff about pixel values.
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Eric Kress Lighting Workshop - part 1 - ASC Web Site

Eric Kress Lighting Workshop - part 1 - ASC Web Site | filmmaking education and training |
For the past 3 years I have organized cinematography workshops & master classes at the Gothenburg Film Studios during their annual Gokinema event. The Danish cinematographer Eric Kress led the first of these workshops, demonstrating the lighting of matched close-ups. This is the first of several posts about Eric’s workshop Eric Kress Eric Kress, DFF,
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BLOG: Don’t Tell Them... Show Them!

BLOG:  Don’t Tell Them... Show Them! | filmmaking education and training |
Don’t Tell Them... Show Them! - blog post by Luis R. Quintero. Tags: Guest Post, Film Festivals, Filmmaking, Advice. Today's guest blog is written by...
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BLOG: Creatives: We're In a League of Our Own

BLOG: Creatives: We're In a League of Our Own | filmmaking education and training |
Creatives: We're In a League of Our Own - blog post by Ron Greenfield. Tags: Guest Post, Inspirational, Advice, Author, Post-Production, Theater. Today I...
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