Hardware Implementation of Face Detection Using ADABOOST Algorithm
Source: IOSR Journal of Engineering
One of the main challenges of computer vision is efficiently detecting and classifying objects in an image or video sequence. Several machine learning approaches have been applied to this problem, demonstrating significant improvements in detection accuracy and speed. However, most approaches have limited object detection to a single class of objects, such as faces or pedestrians. A common benchmark for computer vision researchers is face detection. Given a set of images, a face detection algorithm determines which images have sub-windows containing faces. This task is trivial for humans, but is computationally expensive for machines. Most face detection systems simplify the face detection problem by constraining the problem to frontal views of non-rotated faces.