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  2. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    3D Face image database. 34 action units and 6 expressions labeled; 24 facial landmarks labeled. 4652 Images, text Face recognition, classification 2008 [105] [106] A Savran et al. UOY 3D-Face neutral face, 5 expressions: anger, happiness, sadness, eyes closed, eyebrows raised. labeling. 5250 Images, text Face recognition, classification 2004 ...

  3. 3D Movie Maker - Wikipedia

    en.wikipedia.org/wiki/3D_Movie_Maker

    3D Movie Maker (commonly shortened to 3DMM) is a children's computer program developed by Microsoft Home's Microsoft Kids subsidiary released in 1995. Using the program, users can make films by placing 3D characters and props into pre-rendered environments, as well as adding actions, sound effects, music, text, speech and special effects.

  4. Three-dimensional face recognition - Wikipedia

    en.wikipedia.org/wiki/Three-dimensional_face...

    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.

  5. Viola–Jones object detection framework - Wikipedia

    en.wikipedia.org/wiki/Viola–Jones_object...

    The Viola–Jones object detection framework is a machine learning object detection framework proposed in 2001 by Paul Viola and Michael Jones. [1] [2] It was motivated primarily by the problem of face detection, although it can be adapted to the detection of other object classes. In short, it consists of a sequence of classifiers.

  6. FaceNet - Wikipedia

    en.wikipedia.org/wiki/FaceNet

    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]

  7. Face detection - Wikipedia

    en.wikipedia.org/wiki/Face_detection

    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. [8] AI-assisted emotion detection in faces has gained significant traction in recent years, employing various models to interpret human emotional states.

  8. FaceGen - Wikipedia

    en.wikipedia.org/wiki/FaceGen

    Although FaceGen generates conventional 3D mesh data, it uses a "parameterized" approach to defining the properties that make up a face, and by using a fixed set of parameters it is able to morph and modify a face model independently of output resolution.

  9. Landmark detection - Wikipedia

    en.wikipedia.org/wiki/Landmark_detection

    In computer science, landmark detection is the process of finding significant landmarks in an image. This originally referred to finding landmarks for navigational purposes – for instance, in robot vision or creating maps from satellite images .

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