What are RGB-D cameras? Exploring RGB-D Cameras and Their Significance in Embedded Vision Applications

Table of Contents

1. Introduction

The demand for depth cameras has been on the rise in the domain of embedded vision systems. Many advanced embedded vision applications need accurate depth perception which requires the use of advanced image processing systems. In this article, we will explore the RGB-D cameras as a viable solution for accurate depth perception in embedded vision systems.

1.1: Introduction to RGB-D Cameras

RGB-D (Red Green Blue – Depth) is a specialized camera sensor that captures the depth information of a scene along with the RGB information. This means that the RGB-D camera sensor also determines the distance between the camera lens and the objects in the scene. This additional depth information is invaluable in many applications including 3D mapping, object recognition, gesture recognition, augmented reality, and machine vision. Traditional RGB cameras, on the other hand, only capture RGB information of a scene.

2: How RGB-D Cameras Work?

2.1: Depth Perception in RGB-D Cameras

As described earlier, RGB-D cameras capture the depth information of a scene along with the RGB data. This depth sensing capability of RGB-D cameras makes them highly valuable in applications requiring an understanding of the 3D structure of a scene.

RGB-D cameras deliver RGB and depth information simultaneously in real-time. Therefore, system designers can access the color and depth information of a scene in real-time without any latency. This feature finds its applications in the electric vehicles as well as multiple other industries.

2.2 Depth Maps and Pixel-to-Pixel Merging

By utilizing 3D image sensors, RGB-D cameras are able to generate detailed depth maps of a scene. These cameras employ advanced techniques such as time-of-flight or structured light to determine the distance between the camera lens and the objects in the scene. Hence, the generated image provides an accurate representation of spatial relationships between different objects in the scene.
RGB-D cameras output images in which each pixel provides color as well as depth information in real-time. This highly technical and advanced feature is achieved through an intricate process of pixel-to-pixel merging where color and depth information is seamlessly integrated in real-time.

3: Applications of RBG-D Cameras in Embedded Vision

RGB-D cameras find their applications across multiple sectors and industries including 3D mapping, surveying, healthcare, electric vehicles, and robotics. Some of the prominent application examples of RGB-D cameras are as follows:

3.1: Autonomous Vehicles

RGB-D cameras find their application in the autonomous vehicles for the implementation of ADAS related features such as collision avoidance, object recognition, parking assistant, lane depart assistant, facial recognition, and autopilot.

3.2: Autonomous Mobile Robots

Another exciting application area of RGB-D cameras is mobile robots. RGB-D cameras help the mobile robots in creating a dimensionally correct map of their environment which assists them in obstacle avoidance and optimal path planning.

3.3: Automated Guided Vehicles

AGVs or automated guided vehicles are a hot application area for RGB-D cameras. These vehicles are being increasingly used in warehouses, silos, and factories. As opposed to forklift operators, these vehicles employ advanced sensors and cameras to avoid obstacles, plan the optimal route, and ensure safe transportation and handling of materials.

3.4: Remote Patient Monitoring

RGB-D cameras also play a pivotal role in the healthcare sector. One of the prominent applications of RGB-D cameras in healthcare sector is non-intrusive remote patient monitoring. Healthcare professionals can remotely monitor the movements of patients to provide better healthcare services.

4: Introduction to ToF Technology in RGB-D Cameras

ToF stands for time-of-flight which is a technology for the implementation of highly advanced RGB-D cameras. ToF based camera sensors measure the time it takes for the light to travel back and forth between the camera and the object.

ToF cameras make use of infrared light for scene illumination. The pulses of infrared light are emitted towards the target and the camera sensor precisely measures the time of return for each pulse. By calculating the time it takes for the infrared pulses to return, the camera sensor determines the distance of various objects within its field-of-view.

4.1: Advantages and Limitations of Different RGB-D Technologies

1.Time-of-Flight (ToF):

Measures the time it takes for infrared light pulses to travel to an object and back.

  • Real-time depth measurement
  • Good performance in low light conditions
  • High accuracy and precision
  • Suitable for controlled as well as dynamic environments
  • Limited range compared to other technologies
  • Potential interference from ambient infrared light sources
2.Structured Light:

Projects a pre-defined light pattern onto the scene and evaluates the deformation of the pattern to calculate depth.


  • Higher resolution compared to other technologies
  • Suitable for controlled lighting conditions


  • Interference from external light sources
  • Unsuitable for dynamic environments
  • Complex calibration procedure
3.Stereo Vision:

Uses two or more cameras to calculate depth based on the disparity between corresponding points in the images.

RGB-D camera


  • Good accuracy and resolution
  • Effective for mid-range depth sensing


  • Potential for calibration errors
  • Limited range

5: Conclusion

RGB-D cameras provide a highly sophisticated solution for the accurate and precise measurement of depth information in real time. These cameras capture depth information along with the color data and seamlessly integrate the two in real-time. This capability of RGB-D cameras makes them suitable for multiple applications including ADAS in electric vehicles, autonomous mobile robots, surveying, 3D mapping, gaming, and healthcare. In this article we have explore the working of RGB-D cameras, different technologies used in RGB-D cameras, and application areas of RGB-D cameras. This article serves as an introductory guide for the manufacturers and system designers for the selection of RGB-D cameras for embedded vision applications.

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