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introduction
Introduction
3D vision and 2D vision are two important branches in the field of computer vision, and they have significant differences in data processing, visual perception and application fields. The following will compare 3D vision and 2D vision from several aspects.
PART.01
Data representation and processing
2D vision
The object of 2D vision processing is a flat image or video, which only contains spatial information on the X and Y axes. Each pixel has only two dimensions of information, namely color value and gray level.
3D vision
The objects of 3D vision processing are objects and scenes in three-dimensional space. It contains not only spatial information on the X and Y axes, but also depth information on the Z axis. Through the depth map or point cloud data, more comprehensive information can be obtained, such as: more comprehensive information such as the shape, size and position of the object. Compared with 2D vision, 3D vision can understand objects and scenes more accurately and comprehensively.
PART.02
Spatial and Depth Perception
2D vision
2D vision has limitations in depth perception. It mainly relies on features such as color, shape, and texture for object recognition and monitoring, and cannot directly obtain the depth and three-dimensional sense of objects.
3D vision
3D vision has stronger space and depth perception capabilities, and it can obtain distance and three-dimensional coordinate information of objects through depth maps or point cloud data. This allows it to more accurately locate, measure and reconstruct objects. It has a wide range of applications in robot navigation, 3D reconstruction and other fields.
PART.03
Application field and application effect
2D vision
2D vision has a wide range of applications in many fields, such as image recognition, face recognition, target detection, text recognition, etc. Its processing speed is relatively fast. By analyzing the color, shape and texture of the image, it can efficiently realize object recognition and is suitable for many real-time application scenarios.
3D vision
3D vision has a wider range of applications, such as robot navigation, virtual reality, three-dimensional reconstruction, etc. Compared with 2D vision, 3D vision can provide more accurate and realistic scene perception. By obtaining the depth and stereo information of the object, it is possible to more accurately locate and measure the object and reconstruct the 3D scene. However, due to the high processing complexity, 3D vision usually requires more powerful computing power and complex algorithms to realize.
PART.04
Data acquisition method
2D vision
2D visual data can be obtained by ordinary image sensors or cameras, and information can be obtained by processing images or videos.
3D vision
3D visual data can be acquired in a variety of ways. Depth maps or point cloud data can be obtained through sensors such as structured light, stereo cameras, and lidar. These sensors can provide more dimensional information, however, due to the higher cost, more resources and input may be required in practical applications. But because it can provide more accurate and comprehensive information, it is suitable for tasks that require more precise positioning.
PART.05
Algorithms and Techniques
2D vision
In the field of 2D vision, commonly used algorithms and techniques include edge detection, feature extraction, image segmentation, object recognition, etc. These algorithms are mainly based on the pixel information of the image, and achieve target detection, image segmentation and other tasks by analyzing the relationship and characteristics between pixels.
3D vision
In the field of 3D vision, commonly used algorithms and technologies include depth estimation, point cloud processing, 3D reconstruction, SLAM (Simultaneous Localization and Mapping), etc. These algorithms are mainly based on depth map or point cloud data for analysis and processing.
Source: Machine Vision Network
To sum up, there are obvious differences between 3D vision and 2D vision in many aspects such as data representation and processing methods, spatial perception capabilities, application fields, data acquisition methods, and algorithm technologies.
2D vision is mainly based on two-dimensional image analysis and processing, while 3D vision is widely used in robot navigation and other fields, which can provide more accurate and effective information.
Choosing the right vision technology depends on the specific application requirements and scenarios. In some scenarios, 2D vision is sufficient to meet the needs, while in other scenarios that require more accurate depth perception and positioning, 3D vision is more suitable.
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Author: Xiao Yang Organized by: Sun and Moon
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