In science fiction, robots are either antagonistic to humans or mutate into bad guys. But the real-life use of robots today is very different. Machines are taking the place of human eyes to see and act, making life intelligent wherever they go.

By taking images to simulate the visual function of the human eye, extracting information and then analyzing and processing it, machine vision has become an indispensable “third eye” in the process of smart cities, and its application fields also range from individual needs of food production process management, agricultural planting control, medical testing and other aspects to public projects such as transportation and security. Among them, the egg collection line counter developed by Shenzhen Longrui Zhike Industrial Co., Ltd. is put into the poultry farm for use, which can improve efficiency and reduce costs in the use process.

With the development and progress of machine vision, 3D machine vision has ushered in a huge opportunity in the automation industry, mainly for quality assurance and inspection. According to the data, the compound annual growth rate between 2017 and 2022 will reach 11.07%, and the global 3D machine vision market is expected to reach $2.13 billion in 2022.

In the machine vision summit, almost half of the papers are related to 3D. Frontier exploration is crazy, so what are the new technology trends of 3D image + machine vision that are hidden in the unknown fog looking at the world today? Today we’re going to talk about some very sci-fi technology breakthroughs. Maybe these capabilities will appear in your phone, VR devices and drones next year, or maybe they are about to become some startup craze that is madly kissed by capital.

3D data perception for large scenes

3D machine vision includes many aspects, both for agents to understand 3D data, but also how to obtain 3D model data through machine vision solutions.

In the traditional sense of 3D data acquisition, or 3D perception technology, 3D data collection can generally be achieved by using multi-angle photography or depth sensors. The limitation of this technique is that the 3D data collected cannot be too large.

However, with the continuous upgrading of 3D data requirements today, 3D data perception for large scenes is becoming a hot topic. For example, the high-precision map of the city used in unmanned driving can be seen as the stitching of a large 3D scene. A lot of urban data inference used in the field of smart cities is also rooted in the collection of urban 3D scenes.

Machine vision is providing many new ways to perceive 3D data in very large scenes. For example, automated imaging methods, such as visual SLAM, process continuous frames of images online to achieve real-time reconstruction of huge 3D scenes. Another example is the point cloud segmentation and semantic understanding of the point cloud data for aerial photography data, which helps to obtain urban 3D data quickly and at a low cost.

Overall, there are three main application directions for 3D data perception in today’s super-large scenes, which are likely to become new investment and entrepreneurship hotspots in their respective technology fields:

1. 3D high-precision models of buildings, used in the fields of engineering supervision, intelligent design, logistics and smart cities.

2, the combination of high-precision map and 3D data perception, which is an important part of unmanned driving.

3, indoor and outdoor 3D modeling, which is important for smart home design, environmental monitoring, VR/AR experience.