a blog of links related to computer animation and production technology Sponsored by ReelMatters.com

Category: lighting

  • HDRI shooting and editing by Xuan Prada and Greg Zaal

    www.xuanprada.com/blog/2014/11/3/hdri-shooting

     

    http://blog.gregzaal.com/2016/03/16/make-your-own-hdri/

     

    http://blog.hdrihaven.com/how-to-create-high-quality-hdri/

     

    Shooting checklist

    • Full coverage of the scene (fish-eye shots)
    • Backplates for look-development (including ground or floor)
    • Macbeth chart for white balance
    • Grey ball for lighting calibration
    • Chrome ball for lighting orientation
    • Basic scene measurements
    • Material samples
    • Individual HDR artificial lighting sources if required

    Methodology

    • Plant the tripod where the action happens, stabilise it and level it
    • Set manual focus
    • Set white balance
    • Set ISO
    • Set raw+jpg
    • Set apperture
    • Metering exposure
    • Set neutral exposure
    • Read histogram and adjust neutral exposure if necessary
    • Shot slate (operator name, location, date, time, project code name, etc)
    • Set auto bracketing
    • Shot 5 to 7 exposures with 3 stops difference covering the whole environment
    • Place the aromatic kit where the tripod was placed, and take 3 exposures. Keep half of the grey sphere hit by the sun and half in shade.
    • Place the Macbeth chart 1m away from tripod on the floor and take 3 exposures
    • Take backplates and ground/floor texture references
    • Shoot reference materials
    • Write down measurements of the scene, specially if you are shooting interiors.
    • If shooting artificial lights take HDR samples of each individual lighting source.

    Exposures starting point

    • Day light sun visible ISO 100 F22
    • Day light sun hidden ISO 100 F16
    • Cloudy ISO 320 F16
    • Sunrise/Sunset ISO 100 F11
    • Interior well lit ISO 320 F16
    • Interior ambient bright ISO 320 F10
    • Interior bad light ISO 640 F10
    • Interior ambient dark ISO 640 F8
    • Low light situation ISO 640 F5

     

    NOTE: The goal is to clean the initial individual brackets before or at merging time as much as possible.
    This means:

    • keeping original shooting metadata
    • de-fringing
    • removing aberration (through camera lens data or automatically)
    • at 32 bit
    • in ACEScg (or ACES) wherever possible

     

    Here are the tips for using the chromatic ball in VFX projects, written in English:
    https://www.linkedin.com/posts/bellrodrigo_here-are-the-tips-for-using-the-chromatic-activity-7200950595438940160-AGBp

     

    Tips for Using the Chromatic Ball in VFX Projects**

    The chromatic ball is an invaluable tool in VFX work, helping to capture lighting and reflection data crucial for integrating CGI elements seamlessly. Here are some tips to maximize its effectiveness:

     

    1. **Positioning**:
    – Place the chromatic ball in the same lighting conditions as the main subject. Ensure it is visible in the camera frame but not obstructing the main action.
    – Ideally, place the ball where the CGI elements will be integrated to match the lighting and reflections accurately.

     

    2. **Recording Reference Footage**:
    – Capture reference footage of the chromatic ball at the beginning and end of each scene or lighting setup. This ensures you have consistent lighting data for the entire shoot.

     

    3. **Consistent Angles**:
    – Use consistent camera angles and heights when recording the chromatic ball. This helps in comparing and matching lighting setups across different shots.

     

    4. **Combine with a Gray Ball**:
    – Use a gray ball alongside the chromatic ball. The gray ball provides a neutral reference for exposure and color balance, complementing the chromatic ball’s reflection data.

     

    5. **Marking Positions**:
    – Mark the position of the chromatic ball on the set to ensure consistency when shooting multiple takes or different camera angles.

     

    6. **Lighting Analysis**:
    – Analyze the chromatic ball footage to understand the light sources, intensity, direction, and color temperature. This information is crucial for creating realistic CGI lighting and shadows.

     

    7. **Reflection Analysis**:
    – Use the chromatic ball to capture the environment’s reflections. This helps in accurately reflecting the CGI elements within the same scene, making them blend seamlessly.

     

    8. **Use HDRI**:
    – Capture High Dynamic Range Imagery (HDRI) of the chromatic ball. HDRI provides detailed lighting information and can be used to light CGI scenes with greater realism.

     

    9. **Communication with VFX Team**:
    – Ensure that the VFX team is aware of the chromatic ball’s data and how it was captured. Clear communication ensures that the data is used effectively in post-production.

     

    10. **Post-Production Adjustments**:
    – In post-production, use the chromatic ball data to adjust the CGI elements’ lighting and reflections. This ensures that the final output is visually cohesive and realistic.

    , ,
  • Photography basics: Exposure Value vs Photographic Exposure vs Il/Luminance vs Pixel luminance measurements

    Also see: https://www.pixelsham.com/2015/05/16/how-aperture-shutter-speed-and-iso-affect-your-photos/

     

    In photography, exposure value (EV) is a number that represents a combination of a camera’s shutter speed and f-number, such that all combinations that yield the same exposure have the same EV (for any fixed scene luminance).

     

     

    The EV concept was developed in an attempt to simplify choosing among combinations of equivalent camera settings. Although all camera settings with the same EV nominally give the same exposure, they do not necessarily give the same picture. EV is also used to indicate an interval on the photographic exposure scale. 1 EV corresponding to a standard power-of-2 exposure step, commonly referred to as a stop

     

    EV 0 corresponds to an exposure time of 1 sec and a relative aperture of f/1.0. If the EV is known, it can be used to select combinations of exposure time and f-number.

     

    https://www.streetdirectory.com/travel_guide/141307/photography/exposure_value_ev_and_exposure_compensation.html

    Note EV does not equal to photographic exposure. Photographic Exposure is defined as how much light hits the camera’s sensor. It depends on the camera settings mainly aperture and shutter speed. Exposure value (known as EV) is a number that represents the exposure setting of the camera.

     

    Thus, strictly, EV is not a measure of luminance (indirect or reflected exposure) or illuminance (incidental exposure); rather, an EV corresponds to a luminance (or illuminance) for which a camera with a given ISO speed would use the indicated EV to obtain the nominally correct exposure. Nonetheless, it is common practice among photographic equipment manufacturers to express luminance in EV for ISO 100 speed, as when specifying metering range or autofocus sensitivity.

     

    The exposure depends on two things: how much light gets through the lenses to the camera’s sensor and for how long the sensor is exposed. The former is a function of the aperture value while the latter is a function of the shutter speed. Exposure value is a number that represents this potential amount of light that could hit the sensor. It is important to understand that exposure value is a measure of how exposed the sensor is to light and not a measure of how much light actually hits the sensor. The exposure value is independent of how lit the scene is. For example a pair of aperture value and shutter speed represents the same exposure value both if the camera is used during a very bright day or during a dark night.

     

    Each exposure value number represents all the possible shutter and aperture settings that result in the same exposure. Although the exposure value is the same for different combinations of aperture values and shutter speeds the resulting photo can be very different (the aperture controls the depth of field while shutter speed controls how much motion is captured).

    EV 0.0 is defined as the exposure when setting the aperture to f-number 1.0 and the shutter speed to 1 second. All other exposure values are relative to that number. Exposure values are on a base two logarithmic scale. This means that every single step of EV – plus or minus 1 – represents the exposure (actual light that hits the sensor) being halved or doubled.

    https://www.streetdirectory.com/travel_guide/141307/photography/exposure_value_ev_and_exposure_compensation.html

     

    Formula

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

     

    https://www.scantips.com/lights/math.html

     

    which means   2EV = N² / t

    where

    • N is the relative aperture (f-number) Important: Note that f/stop values must first be squared in most calculations
    • t is the exposure time (shutter speed) in seconds

    EV 0 corresponds to an exposure time of 1 sec and an aperture of f/1.0.

    Example: If f/16 and 1/4 second, then this is:

    (N² / t) = (16 × 16 ÷ 1/4) = (16 × 16 × 4) = 1024.

    Log₂(1024) is EV 10. Meaning, 210 = 1024.

     

    Collecting photographic exposure using Light Meters

    https://photo.stackexchange.com/questions/968/how-can-i-correctly-measure-light-using-a-built-in-camera-meter

    The exposure meter in the camera does not know whether the subject itself is bright or not. It simply measures the amount of light that comes in, and makes a guess based on that. The camera will aim for 18% gray, meaning if you take a photo of an entirely white surface, and an entirely black surface you should get two identical images which both are gray (at least in theory)

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

    For reflected-light meters, camera settings are related to ISO speed and subject luminance by the reflected-light exposure equation:

    where

    • N is the relative aperture (f-number)
    • t is the exposure time (“shutter speed”) in seconds
    • L is the average scene luminance
    • S is the ISO arithmetic speed
    • K is the reflected-light meter calibration constant

     

    For incident-light meters, camera settings are related to ISO speed and subject illuminance by the incident-light exposure equation:

    where

    • E is the illuminance (in lux)
    • C is the incident-light meter calibration constant

     

    Two values for K are in common use: 12.5 (Canon, Nikon, and Sekonic) and 14 (Minolta, Kenko, and Pentax); the difference between the two values is approximately 1/6 EV.
    For C a value of 250 is commonly used.

     

    Nonetheless, it is common practice among photographic equipment manufacturers to also express luminance in EV for ISO 100 speed. Using K = 12.5, the relationship between EV at ISO 100 and luminance L is then :

    L = 2(EV-3)

     

    The situation with incident-light meters is more complicated than that for reflected-light meters, because the calibration constant C depends on the sensor type. Illuminance is measured with a flat sensor; a typical value for C is 250 with illuminance in lux. Using C = 250, the relationship between EV at ISO 100 and illuminance E is then :

     

    E = 2.5 * 2(EV)

     

    https://nofilmschool.com/2018/03/want-easier-and-faster-way-calculate-exposure-formula

    Three basic factors go into the exposure formula itself instead: aperture, shutter, and ISO. Plus a light meter calibration constant.

    f-stop²/shutter (in seconds) = lux * ISO/C

     

    If you at least know four of those variables, you’ll be able to calculate the missing value.

    So, say you want to figure out how much light you’re going to need in order to shoot at a certain f-stop. Well, all you do is plug in your values (you should know the f-stop, ISO, and your light meter calibration constant) into the formula below:

    lux = C (f-stop²/shutter (in seconds))/ISO

     

    Exposure Value Calculator:

    https://snapheadshots.com/resources/exposure-and-light-calculator

     

    https://www.scantips.com/lights/exposurecalc.html

     

    https://www.pointsinfocus.com/tools/exposure-settings-ev-calculator/#google_vignette

     

    From that perspective, an exposure stop is a measurement of Exposure and provides a universal linear scale to measure the increase and decrease in light, exposed to the image sensor, due to changes in shutter speed, iso & f-stop.
    +-1 stop is a doubling or halving of the amount of light let in when taking a photo.
    1 EV is just another way to say one stop of exposure change.

     

    One major use of EV (Exposure Value) is just to measure any change of exposure, where one EV implies a change of one stop of exposure. Like when we compensate our picture in the camera.

     

    If the picture comes out too dark, our manual exposure could correct the next one by directly adjusting one of the three exposure controls (f/stop, shutter speed, or ISO). Or if using camera automation, the camera meter is controlling it, but we might apply +1 EV exposure compensation (or +1 EV flash compensation) to make the result goal brighter, as desired. This use of 1 EV is just another way to say one stop of exposure change.

     

    On a perfect day the difference from sampling the sky vs the sun exposure with diffusing spot meters is about 3.2 exposure difference.

     ~15.4 EV for the sun
     ~12.2 EV for the sky
    

    That is as a ballpark. All still influenced by surroundings, accuracy parameters, fov of the sensor…

     

     

     

    EV calculator

    https://www.scantips.com/lights/evchart.html#calc

    http://www.fredparker.com/ultexp1.htm

     

    Exposure value is basically used to indicate an interval on the photographic exposure scale, with a difference of 1 EV corresponding to a standard power-of-2 exposure step, also commonly referred to as a “stop”.

     

    https://contrastly.com/a-guide-to-understanding-exposure-value-ev/

     

    Retrieving photographic exposure from an image

    All you can hope to measure with your camera and some images is the relative reflected luminance. Even if you have the camera settings. https://en.wikipedia.org/wiki/Relative_luminance

     

    If you REALLY want to know the amount of light in absolute radiometric units, you’re going to need to use some kind of absolute light meter or measured light source to calibrate your camera. For references on how to do this, see: Section 2.5 Obtaining Absolute Radiance from http://www.pauldebevec.com/Research/HDR/debevec-siggraph97.pdf

     

    IF you are still trying to gauge relative brightness, the level of the sun in Nuke can vary, but it should be in the thousands. Ie: between 30,000 and 65,0000 rgb value depending on time of the day, season and atmospherics.

     

    The values for a 12 o’clock sun, with the sun sampled at EV 15.5 (shutter 1/30, ISO 100, F22) is 32.000 RGB max values (or 32,000 pixel luminance).
    The thing to keep an eye for is the level of contrast between sunny side/fill side.  The terminator should be quite obvious,  there can be up to 3 stops difference between fill/key in sunny lit objects.

     

    Note: In Foundry’s Nuke, the software will map 18% gray to whatever your center f/stop is set to in the viewer settings (f/8 by default… change that to EV by following the instructions below).
    You can experiment with this by attaching an Exposure node to a Constant set to 0.18, setting your viewer read-out to Spotmeter, and adjusting the stops in the node up and down. You will see that a full stop up or down will give you the respective next value on the aperture scale (f8, f11, f16 etc.).
    One stop doubles or halves the amount or light that hits the filmback/ccd, so everything works in powers of 2.
    So starting with 0.18 in your constant, you will see that raising it by a stop will give you .36 as a floating point number (in linear space), while your f/stop will be f/11 and so on.

    If you set your center stop to 0 (see below) you will get a relative readout in EVs, where EV 0 again equals 18% constant gray.
    Note: make sure to set your Nuke read node to ‘raw data’

     

    In other words. Setting the center f-stop to 0 means that in a neutral plate, the middle gray in the macbeth chart will equal to exposure value 0. EV 0 corresponds to an exposure time of 1 sec and an aperture of f/1.0.

     

    To switch Foundry’s Nuke’s SpotMeter to return the EV of an image, click on the main viewport, and then press s, this opens the viewer’s properties. Now set the center f-stop to 0 in there. And the SpotMeter in the viewport will change from aperture and fstops to EV.

     

    If you are trying to gauge the EV from the pixel luminance in the image:
    – Setting the center f-stop to 0 means that in a neutral plate, the middle 18% gray will equal to exposure value 0.
    – So if EV 0 = 0.18 middle gray in nuke which equal to a pixel luminance of 0.18, doubling that value, doubles the EV.

    .18 pixel luminance = 0EV
    .36 pixel luminance = 1EV
    .72 pixel luminance = 2EV
    1.46 pixel luminance = 3EV
    ...
    

     

    This is a Geometric Progression function: xn = ar(n-1)

    The most basic example of this function is 1,2,4,8,16,32,… The sequence starts at 1 and doubles each time, so

    • a=1 (the first term)
    • r=2 (the “common ratio” between terms is a doubling)

    And we get:

    {a, ar, ar2, ar3, … }

    = {1, 1×2, 1×22, 1×23, … }

    = {1, 2, 4, 8, … }

    In this example the function translates to: n = 2(n-1)
    You can graph this curve through this expression: x = 2(y-1)  :

    You can go back and forth between the two values through a geometric progression function and a log function:

    (Note: in a spreadsheet this is: = POWER(2; cell# -1)  and  =LOG(cell#, 2)+1) )

    2(y-1) log2(x)+1
    x y
    1 1
    2 2
    4 3
    8 4
    16 5
    32 6
    64 7
    128 8
    256 9
    512 10
    1024 11
    2048 12
    4096 13

     

    Translating this into a geometric progression between an image pixel luminance and EV:

    (more…)

    , ,
  • HDRI Median Cut plugin

    www.hdrlabs.com/picturenaut/plugins.html

     

     

    Note. The Median Cut algorithm is typically used for color quantization, which involves reducing the number of colors in an image while preserving its visual quality. It doesn’t directly provide a way to identify the brightest areas in an image. However, if you’re interested in identifying the brightest areas, you might want to look into other methods like thresholding, histogram analysis, or edge detection, through openCV for example.

     

    Here is an openCV example:

     

    # bottom left coordinates = 0,0
    import numpy as np
    import cv2
    
    # Load the HDR or EXR image
    image = cv2.imread('your_image_path.exr', cv2.IMREAD_UNCHANGED)  # Load as-is without modification
    
    # Calculate the luminance from the HDR channels (assuming RGB format)
    luminance = np.dot(image[..., :3], [0.299, 0.587, 0.114])
    
    # Set a threshold value based on estimated EV
    threshold_value = 2.4  # Estimated threshold value based on 4.8 EV
    
    # Apply the threshold to identify bright areas
    # The luminance array contains the calculated luminance values for each pixel in the image. # The threshold_value is a user-defined value that represents a cutoff point, separating "bright" and "dark" areas in terms of perceived luminance.
    thresholded = (luminance > threshold_value) * 255 
    
    # Convert the thresholded image to uint8 for contour detection 
    thresholded = thresholded.astype(np.uint8) 
    
    # Find contours of the bright areas 
    contours, _ = cv2.findContours(thresholded, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) 
    
    # Create a list to store the bounding boxes of bright areas 
    bright_areas = [] 
    
    # Iterate through contours and extract bounding boxes for contour in contours: 
    x, y, w, h = cv2.boundingRect(contour) 
    
    # Adjust y-coordinate based on bottom-left origin 
    y_bottom_left_origin = image.shape[0] - (y + h) bright_areas.append((x, y_bottom_left_origin, x + w, y_bottom_left_origin + h)) 
    
    # Store as (x1, y1, x2, y2) 
    # Print the identified bright areas 
    print("Bright Areas (x1, y1, x2, y2):") for area in bright_areas: print(area)

     

    More details

     

    Luminance and Exposure in an EXR Image:

    • An EXR (Extended Dynamic Range) image format is often used to store high dynamic range (HDR) images that contain a wide range of luminance values, capturing both dark and bright areas.
    • Luminance refers to the perceived brightness of a pixel in an image. In an RGB image, luminance is often calculated using a weighted sum of the red, green, and blue channels, where different weights are assigned to each channel to account for human perception.
    • In an EXR image, the pixel values can represent radiometrically accurate scene values, including actual radiance or irradiance levels. These values are directly related to the amount of light emitted or reflected by objects in the scene.

     

    The luminance line is calculating the luminance of each pixel in the image using a weighted sum of the red, green, and blue channels. The three float values [0.299, 0.587, 0.114] are the weights used to perform this calculation.

     

    These weights are based on the concept of luminosity, which aims to approximate the perceived brightness of a color by taking into account the human eye’s sensitivity to different colors. The values are often derived from the NTSC (National Television System Committee) standard, which is used in various color image processing operations.

     

    Here’s the breakdown of the float values:

    • 0.299: Weight for the red channel.
    • 0.587: Weight for the green channel.
    • 0.114: Weight for the blue channel.

     

    The weighted sum of these channels helps create a grayscale image where the pixel values represent the perceived brightness. This technique is often used when converting a color image to grayscale or when calculating luminance for certain operations, as it takes into account the human eye’s sensitivity to different colors.

     

    For the threshold, remember that the exact relationship between EV values and pixel values can depend on the tone-mapping or normalization applied to the HDR image, as well as the dynamic range of the image itself.

     

    To establish a relationship between exposure and the threshold value, you can consider the relationship between linear and logarithmic scales:

    1. Linear and Logarithmic Scales:
      • Exposure values in an EXR image are often represented in logarithmic scales, such as EV (exposure value). Each increment in EV represents a doubling or halving of the amount of light captured.
      • Threshold values for luminance thresholding are usually linear, representing an actual luminance level.
    2. Conversion Between Scales:
      • To establish a mathematical relationship, you need to convert between the logarithmic exposure scale and the linear threshold scale.
      • One common method is to use a power function. For instance, you can use a power function to convert EV to a linear intensity value.
      threshold_value = base_value * (2 ** EV)

      Here, EV is the exposure value, base_value is a scaling factor that determines the relationship between EV and threshold_value, and 2 ** EV is used to convert the logarithmic EV to a linear intensity value.

    3. Choosing the Base Value:
      • The base_value factor should be determined based on the dynamic range of your EXR image and the specific luminance values you are dealing with.
      • You may need to experiment with different values of base_value to achieve the desired separation of bright areas from the rest of the image.

     

    Let’s say you have an EXR image with a dynamic range of 12 EV, which is a common range for many high dynamic range images. In this case, you want to set a threshold value that corresponds to a certain number of EV above the middle gray level (which is often considered to be around 0.18).

    Here’s an example of how you might determine a base_value to achieve this:

     

    # Define the dynamic range of the image in EV
    dynamic_range = 12
    
    # Choose the desired number of EV above middle gray for thresholding
    desired_ev_above_middle_gray = 2
    
    # Calculate the threshold value based on the desired EV above middle gray
    threshold_value = 0.18 * (2 ** (desired_ev_above_middle_gray / dynamic_range))
    
    print("Threshold Value:", threshold_value)
    , ,
  • How are Energy and Matter the Same?

    www.turnerpublishing.com/blog/detail/everything-is-energy-everything-is-one-everything-is-possible/

    www.universetoday.com/116615/how-are-energy-and-matter-the-same/

    As Einstein showed us, light and matter and just aspects of the same thing. Matter is just frozen light. And light is matter on the move. Albert Einstein’s most famous equation says that energy and matter are two sides of the same coin. How does one become the other?

    Relativity requires that the faster an object moves, the more mass it appears to have. This means that somehow part of the energy of the car’s motion appears to transform into mass. Hence the origin of Einstein’s equation. How does that happen? We don’t really know. We only know that it does.

    Matter is 99.999999999999 percent empty space. Not only do the atom and solid matter consist mainly of empty space, it is the same in outer space

    The quantum theory researchers discovered the answer: Not only do particles consist of energy, but so does the space between. This is the so-called zero-point energy. Therefore it is true: Everything consists of energy.

    Energy is the basis of material reality. Every type of particle is conceived of as a quantum vibration in a field: Electrons are vibrations in electron fields, protons vibrate in a proton field, and so on. Everything is energy, and everything is connected to everything else through fields.

    ,
  • Cinematographers Blueprint 300dpi poster

    The 300dpi digital poster is now available to all PixelSham.com subscribers.

     

    If you have already subscribed and wish a copy, please send me a note through the contact page.

    , , , ,

Categories


Archive