基于Storm的大容量实时人脸检索系统

针对公共安全领域能够获取的人脸图像数据急速增长，传统的人工方式辨别人物身份工作量大、实时性差、准确度低，本文设计了一种大容量实时人脸检索系统.该系统通过Storm分布式平台实现人脸抓拍图像的实时存储与检索，通过HBase分布式存储系统实现大容量非结构化人脸数据的存储与维护.多组实验结果表明，该系统具有良好的加速比，在大容量人脸图像数据检索场景下具有良好的可扩展性和实时性.

Large-Scale Real-Time Face Retrieval System Based on Storm

The face image data that can be obtained in the field of public security has grown rapidly. The traditional manual method to identify people has large workload, poor real-time performance, and low accuracy. This study designs a large-scale real-time face retrieval system. The system implements the real-time storage and retrieval of captured face images through the distributed platform Storm, and implements the storage and maintenance of large-scale unstructured face data through the distributed storage system HBase. The results of multiple experiments show that the system has a good speedup, good scalability, and real-time performance in the application scenarios of large-scale face image data retrieval.