Face detection

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This article is about Face detection. For Face recognition system, see Facial recognition system. For Human face perception, see Face perception.
Automatic face detection with OpenCV

Face detection is a computer technology that identifies human faces in digital images. It detects human faces which might then be used for recognizing a particular face. This technology is being used in a variety of applications nowadays.

Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene.

Definition and relation to other tasks[edit]

Face detection can be regarded as a specific case of object-class detection. In object-class detection, the task is to find the locations and sizes of all objects in an image that belong to a given class. Examples include upper torsos, pedestrians, and cars.

Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in database. Any facial feature changes in the database will invalidate the matching process.

In human physiology[edit]

Main article: Face perception

Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene.[1] Research shows that our ability to detect faces is affected by a range of visual properties such as color and orientation. [2][3]

Applications[edit]

Facial recognition[edit]

Face detection is used in biometrics, often as a part of (or together with) a facial recognition system. It is also used in video surveillance, human computer interface and image database management.

Photography[edit]

Some recent digital cameras use face detection for autofocus.[4] Face detection is also useful for selecting regions of interest in photo slideshows that use a pan-and-scale Ken Burns effect.

Marketing[edit]

Face detection is gaining the interest of marketers. A webcam can be integrated into a television and detect any face that walks by. The system then calculates the race, gender, and age range of the face. Once the information is collected, a series of advertisements can be played that is specific toward the detected race/gender/age.

An example of such a system is OptimEyes and is integrated into the Amscreen digital signage system[5]

See also[edit]

References[edit]

  1. ^ Lewis, M.B. & Ellis, H.D. (2003). How we detect a face: A survey of the psychological evidence. International Journal of Imaging Systems and Technology, 13, 3-7. DOI: 10.1002/ima.10040
  2. ^ Lewis, M.B. & Edmonds, A.J. (2003). Face detection: Mapping human performance, Perception, 32, 903-920. DOI:10.1068/p5007
  3. ^ Lewis, Michael, and Andrew Edmonds. "Searching for faces in scrambled scenes." Visual Cognition 12.7 (2005): 1309-1336.DOI:10.1080/13506280444000535
  4. ^ "DCRP Review: Canon PowerShot S5 IS". Dcresource.com. Retrieved 2011-02-15. 
  5. ^ Tesco face detection sparks needless surveillance panic, Facebook fails with teens, doubts over Google+ | Technology | theguardian.com

External links[edit]