Single camera vs. multi-camera systems: the ultimate guide

In this blog, you’ll get a complete analysis of both these camera systems, how they work, their similarities and differences, as well as their embedded vision use cases.

What is a single camera system?

A single camera system is an imaging solution that utilises one optical unit to capture visual data. Its functionality centres around processing visual information from a single field of view. These systems are characterised by their streamlined architecture, which simplifies data acquisition and processing.

Single camera setups rely on well-aligned optical and electronic components to convert light into a digital format. This system is ideal for scenarios where depth perception, multiple perspectives, or complex spatial data are unnecessary.

How does a single camera system work?

A single-camera system works in a concise sequence: capturing light, processing it, and sending out the final visual data. Here’s how it all happens:

Light from the scene enters the lens, which focuses it onto the image sensor. It makes sure the captured image is sharp and covers the intended field of view.

Next, the image sensor converts the light into electronic signals, picking up brightness and color to create raw visual data.

Then, the raw data is cleaned up and adjusted: noise is reduced, colours are balanced, and contrast is improved. These adjustments may happen right inside the camera or on a connected device, depending on the setup.

The processed visual data is transmitted to the host system using a compatible communication protocol. The simplicity of the system ensures minimal data latency and straightforward integration with other hardware.

What is a multi-camera system?

A multi-camera system, as the name suggests, incorporates multiple imaging units to capture visual data from different perspectives. This setup is more complex than a single camera system, with its design tailored to offer broader spatial coverage, depth perception, or synchronised multi-angle imaging.

The system integrates multiple cameras that operate in tandem, with each capturing a unique view of the scene. These views are then processed and combined to create a composite visual output or analysed individually, depending on the intended application.

How does a multi-camera system work?

The operation of a multi-camera system involves a series of synchronised steps that enable it to capture and process data:

Each camera in the system captures light from its unique angle or perspective. The positioning of cameras can change based on the intended purpose.

The image sensors in each camera work together to convert light into digital signals. This process occurs independently in each camera unit, with synchronisation through accurate timing mechanisms.

The captured signals are processed to align and combine visual information from all cameras. This stage involves stitching images, calculating depth maps, or isolating specific features in the scene.

The processed data is transmitted to the host system as a unified output or individual streams for further analysis. Advanced algorithms ensure that the data from each camera is aligned accurately to minimise errors or inconsistencies.

Similarities between single camera and multi-camera systems

Purpose: they capture, process, and transmit visual data for analysis or display. Their direct objective is to convert light into a usable format.

Components: both systems rely on image sensors, optical elements, and processing units to achieve their functionality. While the number of these components varies, the technology remains the same.

Signal conversion: no matter the system, light-sensitive sensors, typically CMOS, are used to detect light intensity and colour. The process of converting photons into electronic signals is fundamental to their operation.

Data processing: single camera and multi-camera systems leverage image processing techniques to enhance data quality. Noise reduction, colour correction, as well as exposure adjustment are common, albeit on different scales.

Host system integration: both setups use communication interfaces like USB, MIPI, or Ethernet to transmit data to a host system.

Calibration dependency: proper calibration ensures optimal image quality. Lens alignment, sensor tuning, and colour profiling are also crucial to achieving superior imaging.

Differences between single camera and multi-camera systems

Architecture

Single camera systems use a single optical and sensor unit to capture data within a fixed field of view.

Multi-camera systems use multiple cameras, each capturing data from unique perspectives. They need additional hardware and software to synchronise and process inputs from various units.

Field of view (FoV)

Single camera systems capture data from a single viewpoint, limiting its spatial awareness.

Multi-camera systems offer a broader field of view and the ability to capture data from multiple angles simultaneously.

Depth perception

Single camera systems can’t directly measure depth or create 3D representations without additional computational techniques.

Multi-camera systems enable depth perception and 3D mapping by comparing data from multiple cameras positioned at different locations.

Data complexity

Single camera systems generate a single stream of visual data, simplifying data processing and storage requirements.

Multi-camera systems produce multiple streams of data that require synchronisation, integration, and increased processing power.

Hardware requirements

Single camera systems require minimal hardware, with fewer components to maintain and calibrate.

Multi-camera systems need extra components such as synchronisers, data aggregators, and often more robust processing units.

System flexibility

Single camera systems are best suited for tasks within their field of view.

Multi-camera systems provide greater adaptability, making them capable of handling complex visual tasks requiring multiple inputs.

Synchronisation

Single camera systems operate independently, without the need for synchronisation.

Multi-camera systems demand accurate synchronisation across cameras to ensure accurate data alignment and processing.

Scalability

Single camera systems come with Limited scalability as adding more capabilities requires transitioning to a multi-camera setup.

Multi-camera systems can be scalable by adding more cameras, provided the system can handle the increased data and synchronisation demands.

Embedded vision use cases of single camera systems

Smart traffic systems

Single camera systems play a big role in monitoring traffic flow, detecting violations, and capturing license plate information in smart cities. Their ability to operate in varying lighting conditions and environments makes them perfect for intelligent traffic monitoring setups.

Digital microscopes

In the medical field, single camera systems are embedded in digital microscopes to capture high-resolution images for diagnosis. These systems provide sharp imaging and magnification, making it easy to accurately analyse biological samples.

Industrial scanners

Single camera systems are a part of handheld scanners used in industrial environments. They enable barcode reading, part identification, and inventory management by capturing and processing visual data in real time.

Digital signages

Single camera systems enhance the functionality of digital signages by enabling features such as audience detection, engagement tracking, and targeted content delivery. Their straightforward operation ensures reliability in public spaces.

Embedded vision use cases of multi-camera systems

Smart carts

Multi-camera systems power smart carts by providing accurate visual data for navigation and item recognition. The integration of multiple cameras allows these carts to map environments, detect objects, and operate autonomously in retail or warehouse settings.

Sports broadcasting

In sports broadcasting, multi-camera systems enable automatic tracking of players, ball movement, and action highlights. These systems capture synchronised footage from various angles, providing an exceptional viewing experience.

Pick-and-place robots

Multi-camera systems are important for pick-and-place robots in manufacturing and logistics. They deliver real-time visual data from multiple perspectives for object detection, positioning, and handling in automated workflows.

Delivery robots

Delivery robots rely on multi-camera systems to navigate complex environments, avoid obstacles, and ensure secure package handling. By combining inputs from multiple cameras, these robots achieve the spatial awareness required for autonomous operation.