Position Detection with Face Recognitionusing Image Processing and Machine Learning Techniques
In this paper, an improved algorithm for detecting the position of a person in controlled environments using the face detection algorithm is proposed. This algorithm ingeniously combines different face detection, occlusion detection algorithms, EMD for facial recognition and SVM classifier. A class room environment with thirty students is used along with some constraints such as position of the camera being fixed in a way that covers all the students, the quasi-static student's position and the class environment with the fixed lighting conditions. For every class, a set of 6 attributes are derived and updated in a database. The image is given as an input to the face detection algorithm to detect some of the faces.