Gesture recognition is an area of research and development in computer science and language technology concerned with the recognition and interpretation of human gestures. A subdiscipline of computer vision,^{[citation needed]} it employs mathematical algorithms to interpret gestures.

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 user interfaces (GUIs).

Gestures can originate from any bodily motion or state, but commonly originate from the face or hand. One area of the field is emotion recognition derived from facial expressions and hand gestures. Users can make simple gestures to control or interact with devices without physically touching them.

Many approaches have been made using cameras and computer vision algorithms to interpret sign language, however, the identification and recognition of posture, gait, proxemics, and human behaviors is also the subject of gesture recognition techniques.

Gesture recognition has application in such areas as:

Gesture recognition can be conducted with techniques from computer vision and image processing.

The literature includes ongoing work in the computer vision field on capturing gestures or more general human pose and movements by cameras connected to a computer.

The term "gesture recognition" has been used to refer more narrowly to non-text-input handwriting symbols, such as inking on a graphics tablet, multi-touch gestures, and mouse gesture recognition. This is computer interaction through the drawing of symbols with a pointing device cursor. Pen computing expands digital gesture recognition beyond traditional input devices such as keyboards and mice, and reduces the hardware impact of a system.^[how?]