3D mapping technology is becoming prominent in several industries, from manufacturing and healthcare to agriculture. They enhance imaging capabilities, offering insights previously considered unattainable. There are several types of 3D mapping cameras, including time-of-flight (ToF) cameras, stereo vision cameras, and structured light cameras.
So, which one does your embedded vision application need the most?
In this blog, you’ll find valuable information on these three types of cameras, their key components, and their benefits. You’ll also learn about the popular use cases of 3D mapping – and how modernized applications use this cutting-edge technology.
What is 3D mapping?
3D mapping, also known as three-dimensional mapping, creates a visual representation of an environment or object in three dimensions. It accurately captures the layout, size, and depth, offering a complete and detailed view. The process entails capturing data from the real world and converting it into a digital three-dimensional representation.
The foundation of 3D mapping is the camera technology it employs. At its core, it involves capturing depth information from the surroundings, which typical 2D cameras can’t capture. This depth information is the third dimension, adding a layer of detail crucial for many embedded vision applications.
What are the types of 3D mapping cameras?
Time-of-Flight (ToF) cameras
As the name suggests, time-of-flight cameras determine the distance to an object by measuring the time taken for emitted light to reflect off the object and return. They predominantly consist of:
- A ToF sensor and sensor module that captures and translates light data.
- Typically using VCSEL or LED, a light source emits in the NIR region.
- A depth sensor that processes the raw data, filtering out noise and rendering depth information.
Time-of-flight (ToF) cameras offer a distinct advantage in in-depth mapping and 3D imaging because of their rapid data acquisition speed and high resolution. These cameras, leveraging the principles of light’s speed, can create real-time depth maps, making them invaluable in various applications. Some of the standout features and benefits of ToF cameras include:
- Speed and convenience: ToF cameras can capture depth information in a single shot, allowing for real-time 3D imaging, which is especially useful in dynamic environments.
- Less computational load: Unlike stereo vision systems, ToF cameras do not rely on complex algorithms to compute depth, making them computationally more efficient.
- Ambient light independence: ToF cameras are less affected by ambient lighting conditions, ensuring consistent performance regardless of the external environment.
- Compactness: Their design is generally more compact than other 3D imaging systems, making them suitable for space-constrained applications.
- Versatility: They are used in various applications, from gesture recognition in consumer electronics to obstacle detection in robotics and drones.
Stereo vision cameras
Stereo vision cameras derive their inspiration from human vision. They utilize the depth information deduced from the disparity between images captured by two lenses, mimicking our binocular vision. Key considerations in stereo vision are:
- Baseline: The separation between the two cameras.
- Resolution: The depth is directly linked with resolution. Higher resolution means better depth but requires more processing power.
- Focal length: A balance needs to be struck. A shorter focal length captures more distant objects with a limited field of view.
These cameras capture and correlate two distinct images to render a depth image. They’re particularly useful for outdoor applications with significant fields of view. Some of the advantages of stereo vision cameras are:
- Depth perception: One of the advantages of stereo vision cameras is their ability to provide real-time depth perception. By analyzing the disparity between the two captured images, they can determine objects’ distance and spatial relationship, offering a 3D perspective from 2D images.
- Robustness in varied lighting: Unlike other depth-sensing technologies that may get disrupted in different lighting conditions, stereo vision cameras rely on the disparity between two images, making them less susceptible to variations in ambient lighting.
- Wide Field of View: Given the geometric setup of the two lenses, stereo cameras can provide a broad field of view. This makes them particularly valuable in applications where a comprehensive visual sweep of the environment is essential, such as autonomous driving or surveillance.
- Cost optimization: While delivering reliable depth information, stereo vision cameras often do not require specialized light sources like lasers or infrared, which can make them more affordable compared to some other 3D imaging technologies, especially for outdoor applications.
Structured light cameras
Structured light cameras approach 3D mapping by projecting light patterns onto objects and observing the distortion. Their principle is based on the below factors:
- The camera uses a laser or LED light to cast a structured pattern, often stripes, onto the target.
- When viewed from a different angle, the distortions in these patterns allow the camera to calculate depth.
- This technology is applied in 3D scanning to create detailed digital models of objects.
Some of the advantages of structured light cameras are:
- High accuracy and resolution: Structured light cameras provide high-resolution depth maps because they can capture minute distortions in the projected pattern. This enables the generation of intricate and detailed 3D models, especially for objects closer to the camera.
- Use case versatility: Due to their precision, structured light cameras are preferred in industries where detailed 3D scanning is essential, such as in quality control in manufacturing or medical imaging.
- Performance in controlled environments: In settings where ambient light can be controlled, structured light cameras outperform other depth-sensing techniques by offering reliable and consistent depth measurements devoid of interference from extraneous light sources.
- Design flexibility: The patterns projected by structured light cameras can be altered to suit specific applications. Whether it’s a dense grid for detailed scans or more straightforward patterns for quicker results, the system can be adjusted to the need.
What are the primary use cases of 3D mapping cameras?
Autonomous Mobile Robots (AMR)
Automated transport and deliveries depend on safe navigation, for which they heavily rely on 3D maps. These detailed maps, captured using 3D mapping cameras, provide robots with the depth perception necessary to negotiate obstacles, plan routes, and make real-time decisions, ensuring that the deliveries or guidance they provide are seamless and error-free.
People Counting and Facial Anti-Spoofing Systems
Modern security systems, especially in large establishments and events, deploy 3D cameras to count individuals, offering accurate crowd management insights. Moreover, in the age of digital authentication, ensuring the genuineness of facial recognition is crucial. 3D cameras can discern the depth and contours of faces, playing an instrumental role in detecting and countering spoofing attempts, ensuring an additional layer of security.
Remote Patient Monitoring
Remote patient monitoring, especially in critical care scenarios, demands comprehensive data. With the depth and detail of 3D cameras, healthcare professionals can gain holistic insights into a patient’s condition. This real-time depth monitoring can be instrumental in assessing a patient’s posture, breathing patterns, or movement, ensuring timely and accurate intervention.
Harvesting Robots
Agriculture, one of the oldest professions, is now embracing modern technology. Harvesting robots equipped with 3D vision are revolutionizing the way we collect crops. They utilize the depth perception from 3D mapping cameras to accurately differentiate between ripe and unripe crops. This ensures that only mature crops are harvested, reducing wastage and ensuring maximum yield, leading to optimized agricultural processes.
Patrol Robots
Security concerns in large premises and sensitive areas necessitate constant surveillance. Patrol robots equipped with 3D mapping cameras can autonomously navigate vast environments. The depth information allows these robots to identify obstacles, potential security breaches, and unattended items, ensuring comprehensive security coverage and immediate threat response.
Telepresence Robots
In an increasingly globalized world, being “present” virtually is often as vital as physical presence. Telepresence robots, equipped with 3D cameras, offer users a fully immersive experience. They recreate a three-dimensional virtual environment that mirrors a different location, allowing users to interact and engage as if they were physically present.
3D mapping cameras offered by e-con Systems
e-con Systems has 20+ years of experience in designing, developing, and manufacturing the best-fit camera solutions. Our portfolio includes the DepthVista series, a range of 3D cameras powered by Time-of-Flight technology.
Our ToF cameras operate within the NIR spectrum (940nm/850nm), ensuring reliable 3D capture in both internal and external environments. They offer integrated depth analysis within the camera, instantly producing real-time 2D and 3D information.
Due to high fidelity and precise 3D capture, the DepthVista series is ideal for autonomous robots, self-driving tractors, medical supervision and observation, and 3D facial identification.
The camera range is equipped with three connectivity options: USB, MIPI, and GMSL2. We provide driver and SDK compatibility for NVIDIA Jetson AGX ORIN/AGX Xavier and X86-oriented systems.
Explore our 3D depth camera page
e-con Systems also offers state-of-the-art stereo vision cameras like Tara and TaraXL.
If you need help integrating 3D mapping cameras into your applications, please write to us at camerasolutions@e-consystems.com.
Prabu is the Chief Technology Officer and Head of Camera Products at e-con Systems, and comes with a rich experience of more than 15 years in the embedded vision space. He brings to the table a deep knowledge in USB cameras, embedded vision cameras, vision algorithms and FPGAs. He has built 50+ camera solutions spanning various domains such as medical, industrial, agriculture, retail, biometrics, and more. He also comes with expertise in device driver development and BSP development. Currently, Prabu’s focus is to build smart camera solutions that power new age AI based applications.