keytool分别为服务端与客户端生成公私钥对，并利用java.security包下的工具读取Keystore中的Key，用于创建基于SSL/TLS双向认证的Socket连接，并Java.net包下的Socket与ServerSocket实现一个简单的服务端与客户端之间的通信，该通信模型为BIO模型本文主要使用Java.net包下的Socket与ServerSocket实现一个简单的单服务端与多客户端之间的通信，该通信模型为BIO模型，且不进行SSL/TLS通信加密。
We propose a method to address challenges in unconstrained face detection, such as arbitrary pose variations and occlusions. First, a new image feature called Normalized Pixel Difference (NPD) is proposed. NPD feature is computed as the difference to sum ratio between two pixel values, inspired by the Weber Fraction in experimental psychology. The new feature is scale invariant, bounded, and is able to reconstruct the original image. Second, we propose a deep quadratic tree to learn the optimal subset of NPD features and their combinations, so that complex face manifolds can be partitioned by the learned rules. This way, only a single soft-cascade classifier is needed to handle unconstrained face detection. Furthermore, we show that the NPD features can be efficiently obtained from a look up table, and the detection template can be easily scaled, making the proposed face detector very fast. Experimental results on three public face datasets (FDDB, GENKI, and CMU-MIT) show that the proposed method achieves state-of-the-art performance in detecting unconstrained faces with arbitrary pose variations and occlusions in cluttered scenes.