Face Detection

Face Detection at the Low Light Environments

Today, with the advancement of technology, the use of tools for extracting information from video are much wider in terms of both visual power and the processing power. High-speed car, perfect detection accuracy, business diversity in the fields of medical, home appliances, smart cars, humanoid robots, military systems and the commercialization makes these systems cost effective. Among the most...

Face Detection

Previous Work: Most of the previous work dealt with frontal faces. [1] used clustering to generate face and non-face prototypes. For each test pattern they calculate the distances between the pattern and the prototypes. These distances form the input to a multi-layer perceptron which classifies the pattern into a face and non-face class. In [2] they used a Support Vector Machine (SVM) with a 2n...

Face Detection

Face detection is concerned with finding whether or not there are any faces in a given image (usually in gray scale) and, if present, return the image location and content of each face. This is the first step of any fully automatic system that analyzes the information contained in faces (e.g., identity, gender, expression, age, race and pose). While earlier work dealt mainly with upright fronta...

Face Detection

Face detection in still images and videos has been extensively studied over the last two decades. Attributed to the recent proliferation of cameras in consumer applications, research in face detection has gradually transformed into more unconstrained settings, with the goal of achieving performance close to humans. This presents two main challenges: (i) in addition to modeling the facial charac...

Face Detection