Face detection

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

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

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

Facial recognition

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

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

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

References

  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

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