Region of Interest Tutorial

The Region of Interest (ROI) removes points outside a user-defined region of interest and can reduce capture time. The ROI can either be a box in 3D, a range of z-values from the camera, or both.

A ROI is helpful if the application only requires a portion of the field of view and not the entire scene. If you, for example, want to detect parts in a bin, your detection algorithms may benefit from the reduced search space inside the bin rather than the whole scene.

ROI as a Box

ROI box filtering benefits

ROI box filtering provides one of the following benefits:

Reduced capture time (same point cloud quality)

There is less data to transfer, copy, and process; significant speed-ups are realized with one or both:

• Weak GPU (Intel/Jetson)

• Heavy point cloud processing (Omni/Stripe, 5MP resolution, multi-acquisition HDR)

Better point cloud quality (same capture time)

Different settings can be used; for example:

• Stripe/Omni engine instead of Phase

• Higher resolution with Sampling::Pixel

• Adding more acquisitions in HDR

Cheaper GPU (same capture time)

With less data to process, the processing can be slower, allowing you to use, for example:

• Intel/Jetson instead of dedicated Nvidia

Cheaper Network Card (same capture time)

With less data to transfer you may not saturate the network, allowing you to use, for example:

• 1G instead of 2.5G/10G

• 2.5G instead of 10G

The parameter RegionOfInterest::Box enables using ROI as a box. Three points define the base plane of the box and two extents define the height:

• The three points (Box::PointO, Box::PointA, Box::PointB) are given in the camera frame of reference in 3D and define the base plane of the box. A fourth point is automatically found to bind the base plane into a frame and complete the rectangle. The three points constitute two vectors in order:

  • Point O is the origin of the vectors.

  • Point A spans the first vector from the origin.

  • Point B spans the second vector from the origin.

• The two extents (Box::Extents) extrude the base frame into a box. The cross-product of vectors OA and OB defined by Point O, Point A and Point B gives the direction of the extents. A negative extent will therefore extrude in the opposite direction of the cross-product.

Illustration of the ROI box: Three points (O, A, and B) are given to define the box’s bottom plane, and a fourth point is automatically chosen to complete the rectangle. The bounded plane defined by the four points can then be extruded both upwards (+E2) and downwards (-E1) to complete the box.

Note

The base frame of the box is not constrained to a rectangle with perpendicular corners. It is therefore possible to make a parallelogram as the base, and a parallelepiped as the box.

Tip

Use the following steps when selecting the three points as a rule of thumb:

1. Select Point O in an arbitrary corner.

2. Select Point A such that Point B lies in a position counter-clockwise to Point A.

3. Select Point B in a position counter-clockwise to Point A.

This way the extents will have a positive direction towards the camera.

Configure ROI box in Zivid Studio

Note

When using the point picker you cannot select a pixel that is a NaN in the point cloud. You can therefore only select pixels that correspond to actual points in the point cloud.

Once you have created the ROI box in Zivid Studio you can export the settings YAML and load it back into your application.

C++

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const auto settingsFile = "Settings.yml";
std::cout << "Loading settings from file: " << settingsFile << std::endl;
const auto settingsFromFile = Zivid::Settings(settingsFile);

C#

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var settingsFile = "Settings.yml";
Console.WriteLine("Loading settings from file: " + settingsFile);
var settingsFromFile = new Zivid.NET.Settings(settingsFile);

Python

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settings_file = "Settings.yml"
print(f"Loading settings from file: {settings_file}")
settings_from_file = zivid.Settings.load(settings_file)

ROI box examples and Performance

Robot Picking example

Here is an example of heavy point cloud processing using a low-end PC (Nvidia MX 250 laptop GPU and a 1G network card) where ROI box filtering is very beneficial.

Imagine a robot picking from a 600 x 400 x 300 mm bin with a stationary-mounted Zivid 2+ M130 camera. For good robot clearance, the camera is mounted at 1700 mm distance from the bin top, providing a FOV of approximately 1000 x 800 mm. With the camera mounted at this distance, a lot of the FOV is outside of the ROI, allowing one to crop ~20/25% of pixel columns/rows from each side. As can be seen from the table below, the capture time can be significantly reduced with ROI box filtering.

Presets	Acquisition Time		Capture Time
	No ROI	ROI	No ROI	ROI
Manufacturing Specular	0.64 s	0.64 s	2.1 s	1.0 s
Consumer Goods Quality	0.90 s	0.88 s	5.0 s	3.0 s

Robot Guidance / Assembly example

Here is an example of heavy point cloud processing using a low-end PC (Nvidia MX 250 laptop GPU and a 1G network card) where ROI box filtering is very beneficial.

In some applications in robot guidance (e.g., drilling, welding, gluing) or assembly (e.g., peg-in-hole), the ROI can be very small compared to the FOV of the camera at imaging distance. In such scenarios, with ROIs often comprising only 5-10% of the points in the point cloud, the capture time can drastically be reduced utilizing ROI box filtering (see table below).

Presets	Acquisition Time		Capture Time
	No ROI	ROI	No ROI	ROI
Manufacturing Specular	0.65 s	0.63 s	1.3 s	0.7 s
Manufacturing Small Features	0.70 s	0.65 s	5.0 s	0.8 s

ROI as a Depth Range

The parameter RegionOfInterest::Depth enables to use ROI as a range of z-values from the camera, where points are kept within the following thresholds:

• minimum depth threshold (RegionOfInterest::Depth::minValue)

• maximum depth threshold (RegionOfInterest::Depth::maxValue)

This is useful if you have points in the foreground or background of the scene that you want to filter out. Note that the z-values are given in the camera frame of reference and will therefore filter perpendicularly to the camera. This will thus work best if the camera is mounted perpendicularly to the objects you want to capture.

ROI API

The ROI is a part of the Camera Settings and is set under the Zivid SDK main settings object. It is therefore applied when you capture, and not on the point cloud object afterward.

Tip

ROI as a Box reduces capture time; ROI as a Depth Range does not.

C++

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std::cout << "Configuring settings for capture:" << std::endl;
Zivid::Settings settings{
    Zivid::Settings::Engine::phase,
    Zivid::Settings::Sampling::Color::rgb,
    Zivid::Settings::Sampling::Pixel::all,
    Zivid::Settings::RegionOfInterest::Box::Enabled::yes,
    Zivid::Settings::RegionOfInterest::Box::PointO{ 1000, 1000, 1000 },
    Zivid::Settings::RegionOfInterest::Box::PointA{ 1000, -1000, 1000 },
    Zivid::Settings::RegionOfInterest::Box::PointB{ -1000, 1000, 1000 },
    Zivid::Settings::RegionOfInterest::Box::Extents{ -1000, 1000 },
    Zivid::Settings::RegionOfInterest::Depth::Enabled::yes,
    Zivid::Settings::RegionOfInterest::Depth::Range{ 200, 2000 },
    Zivid::Settings::Processing::Filters::Smoothing::Gaussian::Enabled::yes,
    Zivid::Settings::Processing::Filters::Smoothing::Gaussian::Sigma{ 1.5 },
    Zivid::Settings::Processing::Filters::Noise::Removal::Enabled::yes,
    Zivid::Settings::Processing::Filters::Noise::Removal::Threshold{ 7.0 },
    Zivid::Settings::Processing::Filters::Noise::Suppression::Enabled::yes,
    Zivid::Settings::Processing::Filters::Noise::Repair::Enabled::yes,
    Zivid::Settings::Processing::Filters::Outlier::Removal::Enabled::yes,
    Zivid::Settings::Processing::Filters::Outlier::Removal::Threshold{ 5.0 },
    Zivid::Settings::Processing::Filters::Reflection::Removal::Enabled::yes,
    Zivid::Settings::Processing::Filters::Reflection::Removal::Mode::global,
    Zivid::Settings::Processing::Filters::Cluster::Removal::Enabled::yes,
    Zivid::Settings::Processing::Filters::Cluster::Removal::MaxNeighborDistance{ 10 },
    Zivid::Settings::Processing::Filters::Cluster::Removal::MinArea{ 100 },
    Zivid::Settings::Processing::Filters::Experimental::ContrastDistortion::Correction::Enabled::yes,
    Zivid::Settings::Processing::Filters::Experimental::ContrastDistortion::Correction::Strength{ 0.4 },
    Zivid::Settings::Processing::Filters::Experimental::ContrastDistortion::Removal::Enabled::no,
    Zivid::Settings::Processing::Filters::Experimental::ContrastDistortion::Removal::Threshold{ 0.5 },
    Zivid::Settings::Processing::Filters::Hole::Repair::Enabled::yes,
    Zivid::Settings::Processing::Filters::Hole::Repair::HoleSize{ 0.2 },
    Zivid::Settings::Processing::Filters::Hole::Repair::Strictness{ 1 },
    Zivid::Settings::Processing::Color::Balance::Red{ 1.0 },
    Zivid::Settings::Processing::Color::Balance::Green{ 1.0 },
    Zivid::Settings::Processing::Color::Balance::Blue{ 1.0 },
    Zivid::Settings::Processing::Color::Gamma{ 1.0 },
    Zivid::Settings::Processing::Color::Experimental::Mode::automatic
};
std::cout << settings << std::endl;

C#

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Console.WriteLine("Configuring settings for capture:");
var settings = new Zivid.NET.Settings()
{
    Engine = Zivid.NET.Settings.EngineOption.Phase,
    Sampling = { Color = Zivid.NET.Settings.SamplingGroup.ColorOption.Rgb, Pixel = Zivid.NET.Settings.SamplingGroup.PixelOption.All },
    RegionOfInterest = { Box = {
                            Enabled = true,
                            PointO = new Zivid.NET.PointXYZ{ x = 1000, y = 1000, z = 1000 },
                            PointA = new Zivid.NET.PointXYZ{ x = 1000, y = -1000, z = 1000 },
                            PointB = new Zivid.NET.PointXYZ{ x = -1000, y = 1000, z = 1000 },
                            Extents = new Zivid.NET.Range<double>(-1000, 1000),
                        },
                        Depth =
                        {
                            Enabled = true,
                            Range = new Zivid.NET.Range<double>(200, 2000),
                        }
    },
    Processing = { Filters = { Smoothing = { Gaussian = { Enabled = true, Sigma = 1.5 } },
                               Noise = { Removal = { Enabled = true, Threshold = 7.0 },
                                         Suppression = { Enabled = true },
                                         Repair ={ Enabled = true } },
                               Outlier = { Removal = { Enabled = true, Threshold = 5.0 } },
                               Reflection = { Removal = { Enabled = true, Mode = ReflectionFilterModeOption.Global} },
                               Cluster = { Removal = { Enabled = true, MaxNeighborDistance = 10, MinArea = 100} },
                               Hole = { Repair = { Enabled = true, HoleSize = 0.2, Strictness = 1 } },
                               Experimental = { ContrastDistortion = { Correction = { Enabled = true,
                                                                                      Strength = 0.4 },
                                                                       Removal = { Enabled = true,
                                                                                   Threshold = 0.5 } } } },
                   Color = { Balance = { Red = 1.0, Green = 1.0, Blue = 1.0 },
                             Gamma = 1.0,
                             Experimental = { Mode = ColorModeOption.Automatic } } }
};
Console.WriteLine(settings);

Python

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print("Configuring settings for capture:")
settings = zivid.Settings()
settings.engine = "phase"
settings.sampling.color = "rgb"
settings.sampling.pixel = "all"
settings.region_of_interest.box.enabled = True
settings.region_of_interest.box.point_o = [1000, 1000, 1000]
settings.region_of_interest.box.point_a = [1000, -1000, 1000]
settings.region_of_interest.box.point_b = [-1000, 1000, 1000]
settings.region_of_interest.box.extents = [-1000, 1000]
settings.region_of_interest.depth.enabled = True
settings.region_of_interest.depth.range = [200, 2000]
filters = settings.processing.filters
filters.smoothing.gaussian.enabled = True
filters.smoothing.gaussian.sigma = 1.5
filters.noise.removal.enabled = True
filters.noise.removal.threshold = 7.0
filters.noise.suppression.enabled = True
filters.noise.repair.enabled = True
filters.outlier.removal.enabled = True
filters.outlier.removal.threshold = 5.0
filters.reflection.removal.enabled = True
filters.reflection.removal.mode = "global"
filters.cluster.removal.enabled = True
filters.cluster.removal.max_neighbor_distance = 10
filters.cluster.removal.min_area = 100
filters.experimental.contrast_distortion.correction.enabled = True
filters.experimental.contrast_distortion.correction.strength = 0.4
filters.experimental.contrast_distortion.removal.enabled = False
filters.experimental.contrast_distortion.removal.threshold = 0.5
filters.hole.repair.enabled = True
filters.hole.repair.hole_size = 0.2
filters.hole.repair.strictness = 1
color = settings.processing.color
color.balance.red = 1.0
color.balance.blue = 1.0
color.balance.green = 1.0
color.gamma = 1.0
settings.processing.color.experimental.mode = "automatic"
print(settings)

Tutorials

Check out the below tutorials for examples of how to use the ROI API.

• ROI Box via Zivid Studio
• ROI Box via Checkerboard
• ROI Box via ArUco Marker

For performance information, check out Region of Interest.

Version History

SDK	Changes
2.12.0	ROI box filtering reduces capture time.
2.9.0	ROI API is added.