Abstract
Aimed at the old mode of traditional video surveillance for manual operation and forensics, and the fact that massive amounts of video data occupy a large amount of storage and transmission resources, an intelligent video surveillance architecture based on network and big data is proposed. The architecture includes three core modules: face real-time detecting, face intelligent coding, and face fast retrieval, which can automatically detect human faces, and then intelligently encode them and compare them with databases quickly. It greatly reduces the space occupied by video data storage and transmission, improves the intelligent level of video surveillance, and transforms “after-the-fact analysis” to “in-the-fact analysis” to meet modern criminal investigation requirements.
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