Parallel face analysis platform

In this paper, we proposed an advanced face analysis platform for large-scale consumer photos, namely PFAP. Leveraging Client/Server architecture, the platform provides users high-performance face clustering and near-real time image retrieval service. Advanced face analysis schema, two-level parallel computing architecture and analysis as a service are three key innovations in PFAP. In face analysis part, we employ a semi-supervised face clustering approach and get a good recall and precision. While image analysis is a compute-intensive task, especially in the process of feature extraction, we designed and built a two-level parallel computing system which gets a good speedup and greatly improves the efficiency of the platform. In addition, we packaged some basic operations as services, and then users can submit a job or check the status through a web portal without entering complex commands in the cluster.