Analysis of Single, Dual, Triple, and Multi-Camera Systems

Monocular, binocular, trinocular, and multiocular cameras are key devices in the field of perception, each with its own characteristics and applicable scenarios. Here is a detailed comparison for you:

Composition: It consists of a single lens and image sensor combination, with the simplest structure and relatively low cost.

Principle: It estimates distance and other information based on the size, shape, and texture of in a two-dimensional image, combined with prior knowledge or machine learning models. However, it lacks direct depth measurement methods. For example, in mobile phone photography, monocular camera captures the scene, and through algorithms, it performs simple background blurring on the photographed person or scenery to simulate a shallow depth of field effect.

antage: It is cost-effective and easy to integrate into various small devices, such as home security cameras and children's watch cameras, meeting the basic image acquisition needsLimitation: The accuracy of depth perception is poor, and it cannot accurately judge the distance of objects in complex environments, making it difficult to handle high-precision tasks. For instance, precise obstacle avoidance in autonomous driving cannot rely on a monocular camera.

Composition: It consists of two cameras arranged at certain baseline distance, each with its own optical and imaging system, and it realizes stereo vision by synchronously capturing images.

Principle: Based on the principle ofulation, it uses the disparity between the two cameras shooting the same scene to calculate the depth information of the object, and combines image recognition technology to determine the target. For example, in industrial robot picking operations, a binocular camera helps the robot locate the position and distance of parts, allowing precise picking.

Advantage: to a monocular camera, the depth perception ability is significantly improved, and it can build a relatively simple 3D scene model. It is cost-effective and used in security, robotics, and other fields.

Limitation: It is sensitive to changes in lighting, and the baseline distance needs to be reasonably set; otherwise measurement errors can easily occur. In environments with strong direct light or dim light, the accuracy of depth calculations is greatly affected.

Composition: consists of three cameras arranged in a specific layout, each with its own optical system and image sensor, along with a data processing unit and communication interface.

Principle Similar to a binocular camera, different cameras shoot from multiple angles simultaneously, using rich disparity information to calculate depth with high precision, and combining image recognition to the comprehensive attributes of the target. For example, in autonomous driving, a trinocular camera captures the front road conditions from all directions, accurately perceiving the and category of vehicles, pedestrians, and obstacles.

Advantage: High-precision depth perception, wide-angle coverage without dead zones, and strong target recognition capabilities make suitable for high-end applications that require high accuracy and scene understanding.

Limitation: The camera calibration is complex, the data processing volume is large, and the hardware and technical threshold are high, limiting its popularity in some cost-sensitive fields.

Composition: Comprises four or more cameras, allowing flexible layout design based on different applications, forming a complex visual array.

Principle: Integrates multi-angle and multi-layer image data from various cameras, employs advanced algorithms to mine deep visual information, and constructs ultra-fine3D scene models to achieve high-precision and high-reliability environmental perception. For instance, in professional virtual reality filming, multi-eye cameras are arranged in circle to capture the actor's movements and facial expressions from all directions, endowing the virtual character with realistic expressiveness.

Advantages: Superior environmental perception and detail capabilities, adaptable to extremely complex scenes, and can provide top-tier visual support for cutting-edge technology applications such as the Metaverse and intelligent unmanned systems.

Limit: The system is highly complex, with expensive R&D and production costs, and enormous data processing and transmission pressure. Currently, it is mainly used in high-end research and film production fields.

Overall, as the number of camera eyes increases, visual perception capabilities gradually enhance, but so do costs and technical difficulties. When making selection, it is necessary to consider factors such as application requirements, budget, and technical feasibility to choose the most appropriate visual solution.