Calculate 3D Capture Speed

The time it takes a Zivid camera to capture and process a point cloud is a function of:

Vision engine

Number of acquisitions

Exposure time and aperture of each acquisition

Filters

Processing power of the connected hardware

The calculator allows you to estimate 3D image acquisition time of a Zivid camera. This is the amount of time the camera and scene must remain still relative to each other. The 3D image acquisition time is the time it takes for the capture API to return.

In addition we have benchmarked a number of different settings on different hardware. These results include all of the above.

For more information about the point cloud capture process please see Point Cloud Capture Process.

Estimated 3D image acquisition time:

870 ms

Benchmark acquisition time and processing overhead:

Benchmark acquisition time and processing overhead is only available for presets. Acquisition time added with processing gives the total capture time.

	Low-end ¹	High-end ²
Acquisition	772.2 ms	768.3 ms
Processing	3915.0 ms	134.7 ms

Estimated max bandwidth:

7.07 Gb/s ³

[1] Intel UHD i5G1
[2] NVIDIA 4070 Ti
[3] The `estimated max bandwidth` provides an estimate of how fast your Ethernet connection should be, at a minimum, if you want to achieve the fastest capture speed.

Warning

Be aware that using the Zivid camera at a high duty cycle can trigger thermal throttling to prevent overheating. For more on this topic check out the projector brightness page.

Camera Benchmarks

Below you will find benchmarks of different camera presets with different type of hardware. You can adjust cameras, configuration, and display options to find the data most interesting for you.

Cameras

Configurations

Display Options

Standard Deviation

Capture 2D + 3D (hide)

Manufacturing Settings Parcels Settings Consumer Goods Settings Inspection Settings

hidden

	2+R		2+
	High-end NVIDIA		High-end NVIDIA
	2D	3D	2D	3D
Manufacturing Settings
Manufacturing Diffuse
Manufacturing Semi-Specular
Manufacturing Specular
Manufacturing Small Features

Note

Note that settings with the same name may differ across camera models. For more information about recommended hardware please see Recommended Industrial PCs.

You can check your acquisition and total capture time in Zivid Studio and via the SDK.

C++

const auto frame = camera.capture2D3D(settings);
const auto frameInfo = frame.info();
std::cout << "Acquisition time:" << std::endl;
std::cout << std::chrono::duration_cast<std::chrono::milliseconds>(
                 frameInfo.metrics().acquisitionTime().value())
                 .count()
          << " ms" << std::endl;
std::cout << "Capture time:" << std::endl;
std::cout
    << std::chrono::duration_cast<std::chrono::milliseconds>(frameInfo.metrics().captureTime().value()).count()
    << " ms" << std::endl;

C#

using (var frame = camera.Capture2D3D(settings))
{
    var frameInfo = frame.Info;
    Console.WriteLine("Acquisition time:");
    Console.WriteLine(frameInfo.Metrics.AcquisitionTime.Milliseconds + " ms");
    Console.WriteLine("Capture time:");
    Console.WriteLine(frameInfo.Metrics.CaptureTime.Milliseconds + " ms");

Python

frame = camera.capture_2d_3d(settings)
frame_info = frame.info
print("Acquisition time:")
print(f"{frame_info.metrics.acquisition_time.total_seconds() * 1000:.0f} ms")
print("Capture time:")
print(f"{frame_info.metrics.capture_time.total_seconds() * 1000:.0f} ms")

You can also run our C++ sample ZividBenchmark.cpp to benchmark with your hardware.

Version History

SDK	Changes
2.12.0	Capture time with colors enabled is reduced up to 10-20% with low-end GPUs. 3D acquisition time on Zivid 2+ is reduced by about 5%.
2.9.0	Capture function returns when the acquisition is done.
2.8.0	Improved capture speed of Zivid 2.

Calculate 3D Capture Speed

Select camera model:

Engine:

Sampling:

Acquisitions:

Select preset group:

Select preset: