3D cameras drive machine vision growth

2 May 2024  

Orbbec’s 3D cameras can provide precise measurements of package dimensions, improving logistics and shipping accuracy

3D cameras will drive the global machine vision market over the coming five years, fuelled by strong growth in mobile robot and robotic picking applications. The predicted CAGR for 3D cameras of 13% in the period to 2028 is much higher than the 6.4% CAGR expected for the global machine vision market as a whole (see Fig. 1).

Revenue for 3D machine vision cameras is forecast to grow from $767m in 2022 to almost $1.6bn by 2028, with particularly strong growth expected for time-of-flight and stereo-vision cameras.

Interact Analysis recently published the first edition of a report* on the global machine vision market, which finds that it generated revenues of $6.2bn in 2023 – a 2.8% decline from 2022. Despite this slight contraction, we expect a steady growth rate of 6.4% over the period to 2028, starting with a modest growth of 1.4% this year.

Four technologies

3D cameras can be divided into four main product types, each of which has key features and advantages for different applications.

Structured light 3D cameras project a known pattern or sequence of light onto a surface and analyse the deformation or distortion of this pattern when it interacts with an object. The camera observes how the structured light is deformed and, from this, can calculate the depth and shape of objects in the scene. These cameras are most commonly used when precise measurements and image acquisition are required – such as in bin-picking applications. Structured light 3D cameras are often more expensive than other types of 3D camera. One example of a camera of this type is the Norwegian Zivid 2+ device.

Stereo-vision cameras are equipped with a pair of cameras that perceive depth through binocular disparity. The cameras capture two slightly offset images of the same scene. The disparity between corresponding points in the images is used to calculate depth information for objects in the scene. These cameras are most typically used in robotics and are particularly useful for autonomous driving – an application which offers significant growth potential. One example is Basler’s stereo cameras.

Time-of-flight 3D cameras are imaging devices that determine the distance to objects in a scene by measuring the time it takes for light to travel from the camera to the object and back again. These cameras are typically used when high speed, but lower quality, image acquisition is needed. They are also a cheaper option for mobile robots, enabling them to avoid obstacles and to navigate around other robots. One example of a camera of this type is Lucid’s Helios 2.

Laser triangulation 3D cameras use lasers to measure distances and create three-dimensional representations of objects or scenes. The lasers project a line or pattern onto the target surface, and the camera observes the deformation or displacement of this line/pattern as it interacts with the object. The information captured is then processed to determine the depth or three-dimensional structure of the object. These cameras offer high accuracy and resolution, and are typically used for quality inspection, although they also can also be used to guide mobile robots. An example is LMI’s Chroma-Scan system.

Fig. 2 show expected changes in market share for each type of product in the 3D camera market. What is particularly interesting is the projected growth for stereo-vision and time-of-flight cameras. Although they currently hold just 3% and 2% market shares respectively, this is considerable because these systems are much cheaper than the other two types. We predict a CAGR of 19% for stereo-vision cameras and a CAGR of 17.3% for time-of-flight cameras over the forecast period – far stronger than the forecast for the 3D machine vision camera market as a whole.

Rapid growth

Key factors generating such high growth for 3D cameras, particularly over the longer term, include expected price declines for all types of 3D camera. This will allow users to upgrade their existing systems to 3D cameras, replacing slower, less accurate 2D systems. Strong growth is forecast in particular for robot applications, with a single 3D camera capable of carrying out the same tasks as several 2D cameras, resulting in robots becoming faster and smaller.

Furthermore, the market for 3D cameras is continuing to expand, with many new vendors entering the market each year. This drives prices down, allowing more users to adopt 3D vision systems. Pricing is especially aggressive in China where vendors are selling products at lower prices to gain market share from well-established Western suppliers, driving longer-term growth.

Growth is particularly fast in applications such as autonomous driving and bin-picking (Fig. 3). These two applications have the largest CAGR in our forecast and both really benefit from the use of 3D cameras. Autonomous driving, especially for mobile robots, is an extremely large growth area, with some vendors integrating one (or more) 3D cameras to guide the robot.

Another major growth area for 3D machine vision is bin-picking, including palletising and de-palletising. Substantial year-on-year growth in sales of picking robots is helping to drive rapid expansion of the 3D camera market.

*The Machine Vision 2024 report examines the market for 11 primary products, in 20 industries, for nine applications and in 38 countries.