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Face detection is a binary classification problem combined with a localization problem: given a picture, decide whether it contains faces, and construct bounding boxes for the faces. To make the task more manageable, the Viola–Jones algorithm only detects full view (no occlusion), frontal (no head-turning), upright (no rotation), well-lit ...
The position of these rectangles is defined relative to a detection window that acts like a bounding box to the target object (the face in this case). In the detection phase of the Viola–Jones object detection framework, a window of the target size is moved over the input image, and for each subsection of the image the Haar-like feature is ...
Automatic face detection with OpenCV. Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. [1] Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene.
Face recognition, classification 2011 [104] Zhao, G. et al. BU-3DFE neutral face, and 6 expressions: anger, happiness, sadness, surprise, disgust, fear (4 levels). 3D images extracted. None. 2500 Images, text Facial expression recognition, classification 2006 [105] Binghamton University: Face Recognition Grand Challenge Dataset
Such classifiers can be used for face recognition or texture analysis. A useful extension to the original operator is the so-called uniform pattern, [8] which can be used to reduce the length of the feature vector and implement a simple rotation invariant descriptor. This idea is motivated by the fact that some binary patterns occur more ...
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]
Eigenface provides an easy and cheap way to realize face recognition in that: Its training process is completely automatic and easy to code. Eigenface adequately reduces statistical complexity in face image representation. Once eigenfaces of a database are calculated, face recognition can be achieved in real time.
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]