Parallel Processing for Multi Face Detection and Recognition
Loading...
Authors
Pande, Varun
Elleithy, Khaled M.
Almazaydeh, Laiali
Issue Date
2012-11-14
Type
Article
Language
en_US
Keywords
Face detection , Eye detection , Face recognition , Haar-like features , Principal component analysis (PCA) , Eigenfaces , Roberts cross edge detector , Human computer interaction , Real-time system
Alternative Title
Abstract
In this paper, a robust approach for real time face recognition where the images come from live video is proposed. To improve the algorithmic efficiency of face detection, we combine the eigenface method using Haar-like features to detect both of eyes and face, and Robert cross edge detector to locate the human face position. Robert Cross uses the integral image representation and simple rectangular features to eliminate the need of expensive calculation of multi-scale image pyramid. Moreover, In order to provide fast response in our system, we use Principal Component Analysis (PCA) to reduce the dimensionality of the training set, leaving only those features that are critical for face recognition. Eigendistance is used in face recognition to match the new face while it is projected on the face space. The matching is done when the variation difference between the new image and the stored image is below the threshold value. The experimental results demonstrate that the proposed scheme significantly improves the recognition performance. Overall, we find the system outperforms other techniques. Moreover, the proposed system can be used in different vision-based human computer interaction such as ATM, cell phone, intelligent buildings, etc.
Description
Citation
Publisher
International Society for Computers and Their Applications, Inc.