Computer Vision
Computer vision is a science that studies how to make machines "see". Specifically, it refers to using cameras and computers to replace human eyes to identify, track and measure targets, and using computers to process images into images that are more suitable for human eye observation or transmission to instruments for detection.
definition
Computer vision is a simulation of biological vision using computers and related equipment. Its main task is to obtain two-dimensional or three-dimensional information of the corresponding scene by processing the collected pictures or videos. This is an interdisciplinary subject that has attracted researchers from computer science and engineering, signal processing, physics, applied mathematics and statistics.
principle
Computer vision processes visual information based on the characteristics of computer systems. It uses various imaging systems instead of visual organs as input means, and computers replace the brain to complete processing and interpretation work. The ultimate goal of this technology is to enable computers to understand the world through visual observation like humans, and have the ability to adapt to the environment autonomously.
Related technologies
- Image processing: Image processing technology converts the input image into another image with desired characteristics. Image processing technology is often used for preprocessing and feature extraction in computer vision research.
- Pattern recognition: Pattern recognition technology divides images into predetermined categories based on statistical characteristics or structural information extracted from the images. It is usually used for certain parts of objects in computer vision.
- Image understanding: Given an image, understanding programs need to describe not only the image itself, but also the surrounding scenery in order to make a decision about what the image represents.
application
Computer vision technology is currently used in the following areas:
- Control processes, e.g., industrial robots;
- navigation, for example, by autonomous cars or mobile robots;
- Detected events, e.g., for video surveillance and people counting;
- Organizing information, e.g., indexing databases for images and image sequences;
- Modeling objects or environments, for example, medical image analysis systems or terrain models;
- interaction, e.g., when input into a device for computer-human interaction;
- Automatic inspection, for example, in manufacturing applications.
Related Conferences
- ICCV: International Conference on Computer Vision
- CVPR: International Conference on Computer Vision and Pattern Recognition, International Conference on Computer Vision and Pattern Recognition
- ECCV: European Conference on Computer Vision, European Conference on Computer Vision
- ICIP: International Conference on Image Processing, International Conference on Image Processing
- BMVC: British Machine Vision Conference
- ICPR: International Conference on Pattern Recognition, International Conference on Pattern Recognition
- ACCV: Asian Conference on Computer Vision, Asian Conference on Computer Vision