Machine perception is 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, machine touch, and machine smelling, as artificial scents are, at a chemical compound, molecular, atomic level, indiscernible and identical. The end goal of machine perception is to give machines the ability to see, feel and perceive the world as humans do and therefore for them to be able to explain in a human way why they are making their decisions, to warn us when it is failing and more importantly, the reason why it is failing. This purpose is very similar to the proposed purposes for artificial intelligence generally, except that machine perception would only grant machines limited sentience, rather than bestow upon machines full consciousness, self-awareness, and intentionality.
Machine vision
Computer vision is a field that includes methods for acquiring, processing, analyzing, and understanding images and high-dimensional data from the real world 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. However, machines still struggle to interpret visual impute accurately if it is blurry or if the viewpoint at which stimuli are viewed varies often. Computers also struggle to determine the proper nature of some stimulus if overlapped by or seamlessly touching another stimulus. This refers to the Principle of Good Continuation. Machines also struggle to perceive and record stimulus functioning according to the Apparent Movement principle which is a field of research in Gestalt psychology.
Machine hearing Machine hearing, also known as machine listening or computer audition, is the ability of a computer or machine to take in and process sound data such as speech or music. This area has a wide range of application including music recording and compression, speech synthesis and speech recognition. Moreover, this technology allows the machine to replicate the human brain's ability to selectively focus on a specific sound against many other competing sounds and background noise. This ability is called "auditory scene analysis". The technology enables the machine to segment several streams occurring at the same time. Many commonly used devices such as a smartphones, voice translators and cars make use of some form of machine hearing. Present technology still has challenges in speech segmentation. This means it is occasionally unable to correctly split words within sentences especially when spoken in an atypical accent.
Machine touch
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. Though this could possibly be done through measuring when and where friction occurs and also the nature and intensity of the friction, machines however still do not have any way of measuring few ordinary physical human experiences including physical pain. For example, scientists have yet to invent a mechanical substitute for the Nociceptors in the body and brain that are responsible for noticing and measuring physical human discomfort and suffering. Researchers are exploring ways to combine tactile sensors with machine learning algorithms to approximate human-like touch perception, enabling robots to handle delicate objects, detect texture differences, or respond adaptively to environmental changes. Emerging applications include robotic surgery , prosthetics with sensory feedback, and haptic interfaces in virtual reality, which aim to provide more immersive and precise interaction between humans and machines.
Machine olfaction Scientists are developing computers known as machine olfaction which can recognize and measure smells as well. Airborne chemicals are sensed and classified with a device sometimes known as an electronic nose.
Machine taste
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