Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images into descriptions of the world that make sense to thought processes and can elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory.
A computer mouse is a hand-held pointing device that detects two-dimensional motion relative to a surface. This motion is typically translated into the motion of the pointer on a display, which allows a smooth control of the graphical user interface of a computer.
A pointing device is a human interface device that allows a user to input spatial data to a computer. CAD systems and graphical user interfaces (GUI) allow the user to control and provide data to the computer using physical gestures by moving a hand-held mouse or similar device across the surface of the physical desktop and activating switches on the mouse. Movements of the pointing device are echoed on the screen by movements of the pointer and other visual changes. Common gestures are point and click and drag and drop.
Motion capture is the process of recording the movement of objects or people. It is used in military, entertainment, sports, medical applications, and for validation of computer vision and robots. In filmmaking and video game development, it refers to recording actions of human actors and using that information to animate digital character models in 2D or 3D computer animation. When it includes face and fingers or captures subtle expressions, it is often referred to as performance capture. In many fields, motion capture is sometimes called motion tracking, but in filmmaking and games, motion tracking usually refers more to match moving.
A touchscreen or touch screen is the assembly of both an input and output (display) device. The touch panel is normally layered on the top of an electronic visual display of an electronic device.
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, it employs mathematical algorithms to interpret gestures. 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 is 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.
In visual effects, match moving is a technique that allows the insertion of 2D elements, other live action elements or CG computer graphics into live-action footage with correct position, scale, orientation, and motion relative to the photographed objects in the shot. It also allows for the removal of live action elements from the live action shot. The term is used loosely to describe several different methods of extracting camera motion information from a motion picture. Sometimes referred to as motion tracking or camera solving, match moving is related to rotoscoping and photogrammetry. Match moving is sometimes confused with motion capture, which records the motion of objects, often human actors, rather than the camera. Typically, motion capture requires special cameras and sensors and a controlled environment. Match moving is also distinct from motion control photography, which uses mechanical hardware to execute multiple identical camera moves. Match moving, by contrast, is typically a software-based technology, applied after the fact to normal footage recorded in uncontrolled environments with an ordinary camera.
Video tracking is the process of locating a moving object over time using a camera. It has a variety of uses, some of which are: human-computer interaction, security and surveillance, video communication and compression, augmented reality, traffic control, medical imaging and video editing. Video tracking can be a time-consuming process due to the amount of data that is contained in video. Adding further to the complexity is the possible need to use object recognition techniques for tracking, a challenging problem in its own right.
A wired glove is an input device for human–computer interaction worn like a glove.
Facial motion capture is the process of electronically converting the movements of a person's face into a digital database using cameras or laser scanners. This database may then be used to produce computer graphics (CG), computer animation for movies, games, or real-time avatars. Because the motion of CG characters is derived from the movements of real people, it results in a more realistic and nuanced computer character animation than if the animation were created manually.
Articulated body pose estimation in computer vision is the study of algorithms and systems that recover the pose of an articulated body, which consists of joints and rigid parts using image-based observations. It is one of the longest-lasting problems in computer vision because of the complexity of the models that relate observation with pose, and because of the variety of situations in which it would be useful.
Visual servoing, also known as vision-based robot control and abbreviated VS, is a technique which uses feedback information extracted from a vision sensor to control the motion of a robot. One of the earliest papers that talks about visual servoing was from the SRI International Labs in 1979.
A Hand-Over is a term used in the animation industry to refer to the process of adding finger and hand motion capture data to the pre-existing full-body motion capture data, using a hand motion capture device.
In computing, 3D interaction is a form of human-machine interaction where users are able to move and perform interaction in 3D space. Both human and machine process information where the physical position of elements in the 3D space is relevant.
iClone is a real-time 3D animation and rendering software program. Real-time playback is enabled by using a 3D videogame engine for instant on-screen rendering.
An inertial measurement unit (IMU) is an electronic device that measures and reports a body's specific force, angular rate, and sometimes the orientation of the body, using a combination of accelerometers, gyroscopes, and sometimes magnetometers. When the magnetometer is included, IMUs are referred to as IMMUs.
Project Digits is a Microsoft Research Project under Microsoft's computer science laboratory at the University of Cambridge; researchers from Newcastle University and University of Crete are also involved in this project. Project is led by David Kim a Microsoft Research PhD and also a PhD Student in computer science at Newcastle University. Digits is an input device which can be mounted on the wrist of human hand and it captures and displays a complete 3D graphical representation of the user's hand on screen without using any external sensing device or hand covering material like data gloves. This project aims to make gesture controlled interfaces completely hands free with greater mobility and accuracy. It allows user to interact with whatever hardware while moving from room to room or walking down the street without any line of sight connection with the hardware.
A motion capture suit is a wearable device that records the body movements of the wearer. Some of these suits also function as haptic suits.
In virtual reality (VR) and augmented reality (AR), a pose tracking system detects the precise pose of head-mounted displays, controllers, other objects or body parts within Euclidean space. Pose tracking is often referred to as 6DOF tracking, for the six degrees of freedom in which the pose is often tracked.
