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Computer vision converts images and videos into meaningful information, interpretations, measurements, or actions.
Computer vision is an interdisciplinary scientific and technological field focused on enabling computers to extract, analyze, and understand meaningful information from digital images and videos. It transforms visual data from sources such as cameras, video sequences, 3D scanners, LiDAR, and medical scanners into numerical or symbolic outputs, including descriptions, classifications, measurements, and decisions. Its goal is to automate or support capabilities associated with human vision, using concepts from geometry, physics, statistics, optimization, machine learning, and artificial intelligence. The scope of computer vision includes image acquisition, enhancement, recognition, reconstruction, segmentation, object and event detection, tracking, motion estimation, 3D modeling, pose estimation, and scene understanding. It is applied in medicine, manufacturing, robotics, autonomous navigation, agriculture, military systems, surveillance, augmented reality, multimedia, and accessibility technologies. Although it overlaps with image processing, image analysis, computer graphics, pattern recognition, and machine vision, computer vision generally emphasizes interpreting image content and understanding three-dimensional scenes, while machine vision focuses especially on industrial inspection, process control, and robot guidance.
Computer vision converts images and videos into meaningful information, interpretations, measurements, or actions.
Its methods include image acquisition, processing, recognition, segmentation, tracking, 3D reconstruction, motion analysis, and scene understanding.
The field draws on geometry, physics, statistics, optimization, neuroscience, signal processing, and machine learning, especially deep learning.
Computer vision uses data from cameras, video, multiple viewpoints, 3D scanners, LiDAR, and medical imaging devices.
Major applications include medical diagnosis, industrial quality control, robotics, autonomous vehicles, agriculture, military systems, surveillance, augmented reality, and human-computer interaction.
Computer vision overlaps with image processing and computer graphics but focuses more strongly on interpreting visual content and reconstructing real-world structure.
An interdisciplinary field that develops methods for enabling computers to understand and act on information contained in images and videos.
The application of imaging, analysis, and control technologies to automated inspection, process control, and robot guidance, particularly in industry.
The manipulation of images to enhance, restore, transform, or extract visual features, usually without requiring interpretation of their content.
The process of converting visual data into a meaningful representation of objects, relationships, activities, and three-dimensional structure in a scene.
The task of locating and identifying instances of objects within an image or video.
The division of an image into meaningful regions or pixels associated with particular objects, surfaces, or categories.
The creation of a three-dimensional representation of objects or environments from one or more images or other sensor measurements.
A machine learning approach using multilayer neural networks that has significantly improved performance in tasks such as classification, detection, segmentation, and optical-flow estimation.
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