Volume 6 Issue 3 - January 2016

  • 1. A comprehensive study of face detection and recognition

    Authors : Vinita Malik, Dheeraj Kaushik, Sheetal Srivastava

    Pages : 41-47

    Keywords : Face detection, Feature extraction, Face recognition,Haar-like features, PCA, LDA, ICA, Gabor Wavelet, SVM, Machine Learning, and Neural Networks

    Abstract :

    Over the last decade, face recognition gained magnificent interest in the research field. Face recognition consists of three processes, namely, face detection, feature extraction and recognition. Earlier, face detection is limited to frontal face detection but presently, there are some new algorithms that resolve the problem of side-view detection. In this paper, all the four methods comprising of knowledge-based, template-based, feature-invariant, appearance-based are discussed in detail with the merits and issues they face. Here, we also present short notes on some techniques of face recognition. This includes Haar-like features, Separate Haar, Color-based, PCA, LDA, ICA, SVM, Gabor wavelet, Machine Learning, Neural Networks.This paper also includes a performance comparison of these techniques. To sum up, we have given our conclusion for all the methods of face detection.

    Citing this Journal Article :

    Vinita Malik, Dheeraj Kaushik, Sheetal Srivastava, "A comprehensive study of face detection and recognition", https://www.ijltet.org/journal_details.php?id=898&j_id=2819, Volume 6 Issue 3 - January 2016, 41-47, #ijltetorg