Search results
Results from the WOW.Com Content Network
3D model of a human face. Three-dimensional face recognition (3D face recognition) is a modality of facial recognition methods in which the three-dimensional geometry of the human face is used. It has been shown that 3D face recognition methods can achieve significantly higher accuracy than their 2D counterparts, rivaling fingerprint recognition.
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.
Facial recognition algorithms can help in diagnosing some diseases using specific features on the nose, cheeks and other part of the human face. [75] Relying on developed data sets, machine learning has been used to identify genetic abnormalities just based on facial dimensions. [76] FRT has also been used to verify patients before surgery ...
FaceNet is a facial recognition system developed by Florian Schroff, Dmitry Kalenichenko and James Philbina, a group of researchers affiliated with Google.The system was first presented at the 2015 IEEE Conference on Computer Vision and Pattern Recognition. [1]
Facial recognition can be considered the field that originated the concepts that later on converged into the formalization of the morphable models. The eigenface approach used in face recognition represented faces in a vector space and used principal component analysis to identify the main modes of variation. However, this method had ...
The algorithms for solving this problem are specialized for locating a single pre-identified object, and can be contrasted with algorithms which operate on general classes of objects, such as face recognition systems or 3D generic object recognition. Due to the low cost and ease of acquiring photographs, a significant amount of research has ...
The FRGC was a separate algorithm development project designed to promote and advance face recognition technology that supports existing face recognition efforts in the U.S. Government. One of the objectives of the FRGC was to develop face recognition algorithms capable of performance an order of magnitude better than FRVT 2002.
The Face Recognition Grand Challenge (FRGC) was a project that aimed to promote and advance face recognition technology to support existing face recognition efforts within the U.S. Government. The project ran from May 2004 to March 2006 and was open to face recognition researchers and developers in companies, academia, and research institutions.