Depth Cameras | Overview Depth Cameras

There are different types of 3D sensors, that can differ between different methods to acquire world data or how that data is processed in order to represent it in a convenient way.

These sensors can vary in many ways such as acquisition method, resolution, range, etc. This page entails a brief overview of the different 3D sensor types and a small survey of what sensors are currently available.

João Alves, Aivero

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Last updated: November 16, 2021

Microsoft Azure Kinect

The Aivero team and Azure Kinect

What are depth cameras used for?

Depth sensing cameras enable machines to perceive the environment in three dimensions. Because of the richer information depth cameras provide, they have gained importance in applications such as vision-guided robotics, inspection and monitoring.

3D data is less susceptible to environmental disturbances such as changing light conditions. Thus, machines become more reliable and precise when performing tasks, for example when picking up an object and placing it elsewhere.

Learn more about the use cases of depth cameras

Next we’ll look at how different depth sensors work, covering the most important methods used to generate depth information.

Zivid Two mounted on a collaborative robot

How Do Cameras Detect Depth?

Stereo sensors

Stereo sensors try to mimic human vision by using two cameras facing the scene with some distance between them (baseline, see Figure 1). The images from these cameras are acquired and then used to perform visual feature (relevant visual information) extraction and matching in order to obtain what is called a disparity map between the cameras’ views.

The disparity information is inversely proportional to depth, and can easily be used to obtain the depth map. This also means that some sensors of this type usually only work in feature rich environments and encounter problems in featureless environments (e.g. a white wall). However, this type of sensor, usually allows for greater depth image resolutions than other types of cameras.

These feature detection and matching computations are done on board the camera, which means that they usually require more processing power than other methods. Also, the stereo working distance is limited by the baseline between the cameras as the error increases quadratically with objects’ distance to the sensor. Usual applications entail both indoor or outdoor, feature-rich environments.

Figure 1: Stereo Vision

Time-of-Flight

Time of Flight (ToF) sensors flood the entire scene with light and calculate depth using the time it takes each photon to come back to the sensor. This means that each pixel relates to one beam of light projected by the device, which provides more data density, narrower shadows behind objects and easier calibration (no stereo matching).

Since they use light projection, these sensors are sensitive to different types of surfaces, such as very reflective or very dark ones. In these cases, invalid data usually appears in the image. However they are much more robust to low lighting or dim conditions than stereo sensors which depend on the scene lighting. These sensors can be used both indoors and outdoors.

Structured Light

Structured light (SL) sensors, on the other hand, use a known pattern projected by the IF sensor onto the scene. The way the pattern deforms is then used in constructing the depth map.

This type of sensor does not require an external light source and is mainly used in indoor environments due to their low robustness to sunlight, since interference may occur with the projected light pattern.

Figure 2: Structured Light versus Time of Flight illustration

Light Detection Ranging

Similar to ToF but with scanning, light detection and ranging (LiDAR) sensors are more accurate than ToF since they use multiple IR pulses whereas ToF sensors usually just use one light pulse to obtain their image. By mapping the environment point-per-point instead of a burst of points (as in ToF), the overall noise for each point is reduced, producing more accurate results. Furthermore, LiDAR can usually obtain measurements at a greater distance than traditional ToF or Stereo sensors.

However, LiDAR sensors are usually more expensive than other 3D sensors and, since they perform scanning, can be affected by highly dynamic environments (mo- tion blur).

Figure 3: LiDAR Sensor Operation

Depth Camera Producers

Helios

Producer: Lucid Vision Labs

Type: Time of Flight

Price: N/A

Range: 0.3-6m

Depth Resolutions:

640×480

Color Resolutions:

640×480

Size: 55*55*77.5 mm

Overview of Depth Cameras

What are depth cameras used for?

How Do Cameras Detect Depth?

Stereo sensors

Time-of-Flight

Structured Light

Light Detection Ranging

Depth Camera Producers

Helios

Helios2

Helios2+

Basler Blaze-101

Zivid Two

Dynim Spark

Photoneo Phoxi 3D Scanner

Photoneo MotionCam 3D

Azure Kinect

Ensenso N40 / N45

Ensenso N30 / N35

Ensenso N10

Zivid One+

ZED Stereo Camera

ZED 2 Stereo Camera

ZED Mini Camera

RealSense D415

RealSense D435

RealSense D455

RealSense L515

Astra Mini S

Astra Pro

Astra

Astra S

Astra Stereo S U3

Structure Core

Mynt Eye S210

Mynt Eye S1030

Mynt Eye S1030 Non-ir

Mynt Eye D1000 120 FOV

Mynt Eye D1000 50 FOV

Mynt Eye P

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