Single Camera vs. Multi Camera – Similarities, Differences, and Applications

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Choosing between single camera and multi camera setups has been discussed a lot in the video production world. If you google ‘single camera vs multi camera’, you most likely won’t find many results where the topic has been discussed from the point of view of embedded vision.

At the same time, this is a key consideration in embedded vision, especially in applications where a large FOV (Field Of View) is involved. In today’s article, we dive deep into what the two camera types are, their similarities and differences, the key considerations while choosing a multi camera setup, and some applications where such setups are used.

What is a Single Camera System?

A single camera system, as the term suggests, uses 1 camera module to capture images and videos in embedded vision systems. Engineers choose a single camera system solely based on the features of the camera such as resolution, frame rate, shutter type, chroma (color vs monochrome), dynamic range, focus type (autofocus vs fixed focus), interface, etc.

However, due to the limitations of the field of view, a single camera system may not be able to capture the entire scene or cover a wide area. This can be a limitation for applications that require a broader field of view or monitoring of large spaces.

In most cases, a single camera is not recommended where the FOV is as high as 180 degrees (even with a wide-angle lens) since that might result in lens distortions such as waveform distortion. This also depends on the quality of the lens you use.

What is a Multi Camera System?

Another scenario is where different cameras are used to capture different types of images. For instance, consider a drone used in precision agriculture to measure NDVI (Normalized Difference Vegetation Index). It requires one camera to capture the IR (InfraRed) images while another camera captures images in the visible spectrum.

A Multi-camera system is a setup that uses two or more cameras that can operate either simultaneously (Synchronous) or at different times (Asynchronous) to capture images from various viewpoints.

Multi-camera systems provide richer visual information than single-camera systems, particularly in applications involving recognition and tracking in three-dimensional space.

Synchronous Applications:
Autonomous Vehicles: In self-driving cars, multiple cameras work synchronously to provide a complete 360-degree view of the surroundings, which is crucial for real-time decision-making in navigation and collision avoidance.

Motion Capture Systems: In applications like film production or video game design, multiple cameras capture the movements of actors from various angles at the same time, allowing for a three-dimensional reconstruction of the action.

3D Scanning and Reconstruction: Cameras operate in sync to capture images from different perspectives, making it possible to compute depth information for 3D modeling.

Virtual Reality (VR): VR systems often use multiple cameras operating synchronously to track user movements and adjust the rendered images based on the user’s perspective, creating a highly immersive experience.

Robotic Surgery: Multi-camera systems provide a 3D view during minimally invasive surgeries, operating in sync to offer real-time, detailed imagery that enhances the precision of surgical procedures.

Asynchronous Applications:
Perimeter Security Surveillance: Cameras positioned around a facility’s perimeter could be set to operate at different times or triggered by motion detection to capture activities without the need for simultaneous operation.

Wildlife Monitoring: In wilderness areas, camera systems can be activated by a trigger, such as a motion sensor, capturing images or video of wildlife as they pass by, without all cameras needing to operate synchronously.

Construction Site Monitoring: On construction sites, cameras could be programmed to capture images at different stages or times of the day to monitor progress and observe different work shifts, without requiring synchronous operation.

Traffic Flow Monitoring: In a city traffic monitoring system, cameras installed at different intersections might be set to record at different times of the day to monitor traffic flow and detect violations, operating independently rather than in sync.

Retail Stock Monitoring: In a large retail store, cameras may be set to operate at different times to monitor different sections of the store for inventory management, providing insights on when restocking is needed without having to operate all cameras simultaneously.

Similarities Between a Single Camera and Multi Camera System

In both single camera and multi camera systems, the architecture of an individual camera module remains the same. It comes with a sensor, optical setup, interface, base board, and a connector and image signal processor in some cases. Depending on how the camera is connected to the host system, an additional adapter board might also be required. Whatever the case is, the arrangement of various components is the same in a camera block.

In addition, in both types of cameras, you need to consider the core features – such as resolution, shutter type, frame rate, etc. – while choosing the camera. They are the most critical factors to consider in the selection process.

Differences Between a Single Camera and Multi Camera

This depends on the application and the purpose it serves. The following are some of the key differences between the two camera types:

  • Multi camera systems consume more bandwidth as the interface and host processor must handle the load from multiple cameras. This naturally means that the processor and interface should be capable of delivering high performance. For example, some multi camera systems will need high-end processors like NVIDIA Jetson AGX Orin or NVIDIA Jetson AGX Xavier.

  • Multi camera systems tend to be more expensive, not just because of the increase in the number of cameras, but also because of the higher complexity of integration and setup.

  • A multi camera system need not always use multiple cameras of the same type. Some applications could use one camera for a specific task and another for a different task.

Key Considerations While Choosing a Multi Camera

Selecting and integrating a multi camera system is more complex than one with a single camera. Here is a quick overview of the factors you need to consider while doing this:

  • Field of View: The FOV can influence the number of cameras needed. When you require a wide FOV with low distortion, it is recommended to use more than two cameras for image stitching.

  • The capacity of the interface and the host processor: Depending on the size of the image/video file from each camera, you might have to use a high bandwidth interface like MIPI CSI-2 or FPD-Link III. When it comes to host platforms, powerful processors like NVIDIA Jetson and TI Jacinto TDA4VM are commonly used in multi camera systems.

  • Synchronous operation: In multi-camera applications, especially where image stitching is required, multiple cameras need to operate synchronously to allow the image processor and computer vision algorithms to generate a well-stitched final image.

You need to note that all the other camera parameters that you take into account while choosing a single camera come into play here as well. What we discussed just now is the set of parameters you need to consider additionally.

Applications of a Single Camera System

As a matter of fact, there is no point in calling out the applications of single camera systems because almost any embedded vision system could use one, except those which need multiple cameras.

But here are a few modern embedded vision applications where a single camera system can be used:

  • Smart traffic systems
  • Biometric and security systems
  • Medical microscopes
  • Document readers
  • Industrial handheld scanners
  • Eye diagnostic devices
  • Digital signage and displays
  • Patient monitoring devices
  • Surveillance systems

It is important to note that it is very difficult to generalize and say one umbrella application can use only a single camera system. For example, a smart traffic device could use multiple cameras if the scene of interest has a large field of view. Every application is unique, and you need to treat them differently.

Applications of Multi Camera Systems

Embedded vision devices are advancing every day, and applications needing multiple cameras are also on the rise. If you look at modern embedded vision applications, you will see that many of them require multiple cameras. Let us learn more about some of them here.


Robotics is vast. Robots are used in almost every sector of our life. With the onslaught of AI, only the sky is the limit for what robots can do. 99% of robots need multiple cameras.

In most cases, robotic vision systems use multiple cameras for different purposes, for example, one for navigation and another for capturing barcodes.

Concerning the extent of warehouse automation, robots can be classified into two categories: AMRs (Autonomous Mobile Robots) which navigate completely autonomously, and AGVs (Automated Guided Vehicles), which rely on guided paths for navigation. Both use multi camera systems.

A few additional examples of robots that use multi camera systems are:

  • Delivery robots
  • Cleaning robots
  • Automated weeders
  • Pick and place robots
  • Telepresence robots
  • Companion robots


Drones are finding applications in construction, film production, inspection, and many other key industrial, commercial, and household domains. They rely on camera modules to capture images and videos for broadcasting and performing various kinds of analyses.

Like robots, some drones use cameras for more than one purpose. While one camera can be used for obstacle detection, another one can be used for image capture. It all depends on the use case of the device.

Given below are a few types of drones categorized as per their application where multiple cameras are used:

  • Inventory tracking drones used in warehouses and retail stores
  • Inspection drones used in construction, mining, and insurance
  • Delivery drones used for D2C delivery
  • Military drones used for surveillance and defense
  • Agricultural drones

Autonomous Shopping

As mentioned earlier, autonomous shopping systems are used to identify objects – whether they are placed at the checkout counter or the shopping cart – utilizing multiple cameras to be able to capture objects from different angles.

Both barcode-based and computer vision-based object identification systems require multi-camera setups.

Airport Baggage Systems

Apart from robots, there are other types of agricultural and industrial vehicles where multi-cameras are used. Examples include:

  • Tractors: Cameras are used to assist in plowing, soil analysis, and crop monitoring
  • Forklifts: Forklifts can operate completely autonomously with the help of cameras
  • Mining vehicles and trucks: They use cameras primarily as a safety system to eliminate blind spots.

Airport baggage systems use cameras for the following tasks:

  • Counting the number of bags
  • Classifying bags by type
  • Identifying bags by barcode so that they can be routed
  • Identifying empty bag trays at the time of security check-in.

For some tasks, a single camera might be enough, while other tasks require multiple cameras are usually needed to cover the entire field of view, or the bags from multiple angles.

Automated Dimensioning and Weight Measurement Systems

Automated dimensioning systems use cameras to accurately measure the dimensions of objects in a warehouse, retail store, or factory. One of the methods of achieving this is using cameras as stereo pairs to measure depth. The dimension of the object is then calculated from the depth information to arrive at the dimensions and weight of the object. Mutiple cameras may be used to measure the 3D shape of an object from different angles.

Agricultural and Industrial Vehicles

Apart from robots, there are other types of agricultural and industrial vehicles where multi cameras are used. Examples include:

  • Tractors: Cameras are used to assist in plowing, soil analysis, and crop monitoring
  • Forklifts: Forklifts can operate completely autonomously with the help of cameras
  • Mining vehicles and trucks: They use cameras primarily as a safety system to eliminate blind spots.

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