Face detection is a computer technology being used in a variety of applications that identifies human faces in

digital image A digital image is an image composed of picture elements, also known as pixels, each with '' finite'', '' discrete quantities'' of numeric representation for its intensity or gray level that is an output from its two-dimensional functions f ...

s. Face detection also refers to the

psychological Psychology is the scientific study of mind and behavior. Its subject matter includes the behavior of humans and nonhumans, both consciousness, conscious and Unconscious mind, unconscious phenomena, and mental processes such as thoughts, feel ...

process by which humans locate and attend to faces in a visual scene.

Definition and related algorithms

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 simply answers two question, 1. are there any human faces in the collected images or video? 2. where is the face located? 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. A reliable face-detection approach based on the

genetic algorithm In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to g ...

and the eigen-face technique: Firstly, the possible human eye regions are detected by testing all the valley regions in the gray-level image. Then the genetic algorithm is used to generate all the possible face regions which include the eyebrows, the iris, the nostril and the mouth corners. Each possible face candidate is normalized to reduce both the lighting effect, which is caused by uneven illumination; and the shirring effect, which is due to head movement. The fitness value of each candidate is measured based on its projection on the eigen-faces. After a number of iterations, all the face candidates with a high fitness value are selected for further verification. At this stage, the face symmetry is measured and the existence of the different facial features is verified for each face candidate.

Applications

Facial motion capture

Facial recognition

Face detection is used in

biometrics Biometrics are body measurements and calculations related to human characteristics and features. Biometric authentication (or realistic authentication) is used in computer science as a form of identification and access control. It is also used t ...

, often as a part of (or together with) a

facial recognition system A facial recognition system is a technology potentially capable of matching a human face from a digital image or a Film frame, video frame against a database of faces. Such a system is typically employed to authenticate users through ID verif ...

. It is also used in

video surveillance Closed-circuit television (CCTV), also known as video surveillance, is the use of closed-circuit television cameras to transmit a signal to a specific place on a limited set of monitors. It differs from broadcast television in that the signal ...

, human computer interface and image database management.

Photography

Some recent digital cameras use face detection for autofocus. Face detection is also useful for selecting regions of interest in photo slideshows that use a pan-and-scale Ken Burns effect. Modern appliances also use smile detection to take a photograph at an appropriate time.

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.

Emotional Inference

Face detection can be used as part of a software implementation of emotional inference. Emotional inference can be used to help people with autism understand the feelings of people around them. AI-assisted emotion detection in faces has gained significant traction in recent years, employing various models to interpret human emotional states. OpenAI's CLIP model exemplifies the use of deep learning to associate images and text, facilitating nuanced understanding of emotional content. For instance, combined with a network psychometrics approach, the model has been used to analyze political speeches based on changes in politicians' facial expressions. Research generally highlights the effectiveness of these technologies, noting that AI can analyze facial expressions (with or without vocal intonations and written language) to infer emotions, although challenges remain in accurately distinguishing between closely related emotions and understanding cultural nuances.

Lip Reading

Face detection is essential for the process of language inference from visual cues. Automated lip reading has applications to help computers determine who is speaking which is needed when security is important.

References

External links

Detecting faces in images: a survey

Face detection and Recognition: Online Demonstration
{{DEFAULTSORT:Face Detection Facial recognition Object recognition and categorization de:Gesichtserkennung