Human–computer interaction (HCI) is research in the design and the use of computer technology, which focuses on the interfaces between people (users) and computers. HCI researchers observe the ways humans interact with computers and design technologies that allow humans to interact with computers in novel ways. A device that allows interaction between human being and a computer is known as a "Human-computer Interface (HCI)".
As a field of research, human–computer interaction is situated at the intersection of computer science, behavioral sciences, design, media studies, and several other fields of study. The term was popularized by Stuart K. Card, Allen Newell, and Thomas P. Moran in their 1983 book, The Psychology of Human–Computer Interaction. The first known use was in 1975 by Carlisle. The term is intended to convey that, unlike other tools with specific and limited uses, computers have many uses which often involve an open-ended dialogue between the user and the computer. The notion of dialogue likens human–computer interaction to human-to-human interaction: an analogy that is crucial to theoretical considerations in the field. (Full article...)
Gesture recognition offers a path for computers to begin to better understand and interpret human body language, previously not possible through text or unenhanced graphical (GUI) user interfaces. (Full article...)
The following are images from various human–computer interaction-related articles on Wikipedia.
Image 1The skeletal version (right) is effectively modeling the hand (left). This has fewer parameters than the volumetric version and it's easier to compute, making it suitable for real-time gesture analysis systems. (from Gesture recognition)
Image 2A VPL Research DataSuit, a full-body outfit with sensors for measuring the movement of arms, legs, and trunk. Developed c. 1989. Displayed at the Nissho Iwai showroom in Tokyo (from Virtual reality)
Image 3View-Master, a stereoscopic visual simulator, was introduced in 1939.
Image 5A child's hand location and movement being detected by a gesture recognition algorithm (from Gesture recognition)
Image 6Virtual Fixtures immersive AR system developed in 1992. Picture features Dr. Louis Rosenberg interacting freely in 3D with overlaid virtual objects called 'fixtures'. (from Virtual reality)
Image 9An Omni treadmill being used at a VR convention (from Virtual reality)
Image 10A real hand (left) is interpreted as a collection of vertices and lines in the 3D mesh version (right), and the software uses their relative position and interaction in order to infer the gesture. (from Gesture recognition)
Image 11Robinson R22 Virtual Reality Training Device developed by Loft Dynamics (from Virtual reality)
Image 12An operator controlling The Virtual Interface Environment Workstation (VIEW) at NASAAmes around 1990 (from Virtual reality)
Image 13A CAVE system at IDL's Center for Advanced Energy Studies in 2010 (from Virtual reality)
Image 19Some alternative methods of tracking and analyzing gestures, and their respective relationships (from Gesture recognition)
Image 20Middleware usually processes gesture recognition, then sends the results to the user. (from Gesture recognition)
Image 21These binary silhouette(left) or contour(right) images represent typical input for appearance-based algorithms. They are compared with different hand templates and if they match, the correspondent gesture is inferred. (from Gesture recognition)
Image 22The user interacts directly with hardware for the human input and output such as displays, e.g. through a graphical user interface. The user interacts with the computer over this software interface using the given input and output (I/O) hardware. Software and hardware are matched so that the processing of the user input is fast enough, and the latency of the computer output is not disruptive to the workflow. (from Human–computer interaction)