31-08-2017, 11:33 AM
Object recognition is the area of artificial intelligence (AI) that deals with the abilities of robots and other implementations of AI to recognize various things and entities.
Object recognition allows AI robots and programs to select and identify objects from inputs such as video images and still cameras. Methods used for object identification include 3D models, component identification, edge detection and appearance analysis from different angles.
Object recognition is at the convergence points of robotics, machine vision, neural networks and AI. Google and Microsoft are among the companies working in the area - Google's driverless car and Microsoft's Kinect system use object recognition.
Robots who understand their environments can perform more complex tasks better. Great advances in object recognition can revolutionize AI and robotics:
• MIT has created neural networks, based on our understanding of how the brain works, which allow software to identify objects almost as quickly as primates do.
• Visual data gathered from robotics in the cloud can allow several robots to learn tasks more quickly associated with object recognition. Robots can also refer to massive databases of known objects, and that knowledge can be shared among all connected robots.
• Scientists at Brigham Young University have developed an object recognition algorithm that can learn to identify objects by itself. The Evolution-Constructed Features algorithm, as it is called, can make decisions about what characteristics of an object are relevant to its identification.
Concerns about the potential for object recognition include the fear that advertisers and other interested parties may use the technology to extract the growing number of images posted online and collect personal information from individuals.
Object recognition allows AI robots and programs to select and identify objects from inputs such as video images and still cameras. Methods used for object identification include 3D models, component identification, edge detection and appearance analysis from different angles.
Object recognition is at the convergence points of robotics, machine vision, neural networks and AI. Google and Microsoft are among the companies working in the area - Google's driverless car and Microsoft's Kinect system use object recognition.
Robots who understand their environments can perform more complex tasks better. Great advances in object recognition can revolutionize AI and robotics:
• MIT has created neural networks, based on our understanding of how the brain works, which allow software to identify objects almost as quickly as primates do.
• Visual data gathered from robotics in the cloud can allow several robots to learn tasks more quickly associated with object recognition. Robots can also refer to massive databases of known objects, and that knowledge can be shared among all connected robots.
• Scientists at Brigham Young University have developed an object recognition algorithm that can learn to identify objects by itself. The Evolution-Constructed Features algorithm, as it is called, can make decisions about what characteristics of an object are relevant to its identification.
Concerns about the potential for object recognition include the fear that advertisers and other interested parties may use the technology to extract the growing number of images posted online and collect personal information from individuals.