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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.
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.
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]
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.
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.
Michael Dean of Game Developer commended the 2.2 version of FaceGen as a "robust package" for the customizability of its settings, the ease of creating faces that "differ greatly" from one another, and its efficiency compared to manually modelling a face. [1] Sean Wagstaff praised the 3.0 version in a later publication for its "reasonably ...
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
In order to make it available on all major operating systems, beginning from 1.0 alpha 8 it's developed in Python using OpenGL and Qt, with an architecture fully realized with plugins. The tool is specifically designed for the modeling of virtual 3D human models, with a simple and complete pose system that includes the simulation of muscular ...