Machine perception is a term that is used to identify the capability of a computer system to interpret data in a manner that is similar to the way humans use their senses to relate to the world around them. The basic method that the computers take in and respond to their environment is through the attached hardware. Until recently input was limited to a keyboard, or a mouse, but advances in technology, both in hardware and software, have allowed computers to take in sensory input in a way similar to humans.
Machine perception allows the computer to use this sensory input, as well as conventional computational means of gathering information to gather information with greater accuracy and to present it in a way that is more comfortable for the user. These include computer vision, machine hearing, and machine touch.
Computer vision is a field that includes methods for acquiring, processing, analyzing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions. Computer vision has many applications already in use today such as facial recognition, geographical modeling, and even aesthetic judgment.
Machine hearing, or Computer audition is the ability of a computer or machine to take in and process sound data such as music or speech. This area has a wide range of application including music recording and compression, speech synthesis, and speech recognition. Many commonly used devices such as a smartphones, voice translators, and even cars make use of some form of machine hearing.
Machine touch is an area of machine perception where tactile information is processed by a machine or computer. Applications include tactile perception of surface properties and dexterity whereby tactile information can enable intelligent reflexes and interaction with the environment.
- Malcolm Tatum (October 3, 2012). "What is Machine Perception".
- Alexander Serov (January 29, 2013). "Subjective Reality and Strong Artificial Intelligence".
- Sagnik Dhar, Vicente Ordonez, and Tamara L Berg (2011). "High Level Describable Attributes for Predicting Aesthetics and Interestingness". Computer Vision and Pattern Recognition (CVPR), 2011 IEEE. pages 1657 - 1664
- Richard F. Lyon (September 2010). "Machine Hearing: An Emerging Field". IEEE SIGNAL PROCESSING MAGAZINE.
- Turk, Matthew (2000). "Perceptive Media: Machine Perception and Human Computer Interaction". Chinese Journal of Computers 12. pages 1235-1244