Automated Vision Task
(Redirected from Computer Vision)
Jump to navigation
Jump to search
An Automated Vision Task is a vision task that must be an automated task.
- Context:
- It can be solved by a Computer Vision System (that implements a computer vision algorithm).
- It can range from being a Static Computer Vision Task to being a Moving Computer Vision Task (such as for robot vision).
- It can be a research topic within an Computer Vision Research Discipline.
- …
- Example(s):
- Counter-Example(s):
- See: Object Detection Task, Object Recognition Task, Computer Vision Discipline, Mobile Robot, Machine Vision, Automated Species Identification, Industrial Robots, Activity Recognition, Artificial Intelligence for Video Surveillance, People Counter, Presto (Restaurant Technology), Computer-Human Interaction, Autonomous Vehicle, Computer-Assisted Diagnosis, Tumour.
References
2020
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Computer_vision#Applications Retrieved:2020-8-13.
- Applications range from tasks such as industrial machine vision systems which, say, inspect bottles speeding by on a production line, to research into artificial intelligence and computers or robots that can comprehend the world around them. The computer vision and machine vision fields have significant overlap. Computer vision covers the core technology of automated image analysis which is used in many fields. Machine vision usually refers to a process of combining automated image analysis with other methods and technologies to provide automated inspection and robot guidance in industrial applications. In many computer-vision applications, the computers are pre-programmed to solve a particular task, but methods based on learning are now becoming increasingly common. Examples of applications of computer vision include systems for:
- Automatic inspection, e.g., in manufacturing applications;
- Assisting humans in identification tasks, e.g., a species identification system;
- Controlling processes, e.g., an industrial robot;
- Detecting events, e.g., for visual surveillance or people counting, e.g., in the restaurant industry;
- Interaction, e.g., as the input to a device for computer-human interaction;
- Modeling objects or environments, e.g., medical image analysis or topographical modeling;
- Navigation, e.g., by an autonomous vehicle or mobile robot; and
- Organizing information, e.g., for indexing databases of images and image sequences.
- Applications range from tasks such as industrial machine vision systems which, say, inspect bottles speeding by on a production line, to research into artificial intelligence and computers or robots that can comprehend the world around them. The computer vision and machine vision fields have significant overlap. Computer vision covers the core technology of automated image analysis which is used in many fields. Machine vision usually refers to a process of combining automated image analysis with other methods and technologies to provide automated inspection and robot guidance in industrial applications. In many computer-vision applications, the computers are pre-programmed to solve a particular task, but methods based on learning are now becoming increasingly common. Examples of applications of computer vision include systems for:
2020
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/computer_vision Retrieved:2020-8-13.
- Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do.
Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. ...
- Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do.