Affiliation:
1. Faculty of Computers and Artificial Intelligence, Beni-Suef University, Egypt
Abstract
Web content is diverse and is regarded as the primary source of accessible information that can be accessed through reference links. Web facial images are one type of web content that relates to important web pages and is considered important information for individuals. This chapter proposes face recognition as a service architecture that is based on real-world images from the web. The proposed service is implemented as a service for other third parties via cloud computing; additionally, its architecture is built via cloud using virtual machines that can be expanded based on resource demands. Web crawlers crawl web pages and retrieve images for elastic cloud storage. The collected images are then used to remove human faces and prepare the face images for identification and identifying the matched face of the set through successive phases. This chapter used PCA for features extraction and KNN for identification. Experiments show that increasing the number of crawler instances improves crawling speed and improves face recognition accuracy by preferring Euclidean over other metrics.
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