视频侦查中人像智能分析应用及算法优化

Portrait Intelligent Analysis Application and Algorithm Optimization in Video Investigation

人像智能分析指的是对视频或录像中的人像进行结构化和可视化分析,对目标人物进行性别、年龄、发型等特征的智能识别,这项技术在视频侦查中有极高的应用价值。人像识别早期的算法是通过人工提取特征,通过学习低级视觉特征来针对不同属性进行分类学习,这种基于传统方法的模型表现常常不尽如人意。在计算机视觉领域,通过海量图像数据学习的神经网络比传统方法有更丰富的信息量和特征可以被提取。文章尝试通过深度学习技术训练神经网络模型对行人进行检测和识别,对于衣着不同的行人进行智能识别,具有更好的鲁棒性,提升了视频人像识别的准确率,拓展了人工智能技术在身份识别领域的应用。

Intelligent portrait analysis refers to the structural and visual analysis of portraits in video or video,and intelligent identification of the target person’s gender,age,hairstyle,etc.This technology has extremely high application value in video reconnaissance.The early algorithm of portrait recognition is to manually extract features and learn low-level visual features to classify and learn different attributes.This model based on traditional methods is often not satisfactory.In the field of computer vision,neural networks learned from massive image data have richer information and feature extraction than traditional methods.This paper attempts to train neural network models to detect and recognize pedestrians through deep learning technology,and intelligently treat pedestrians with different clothes.Recognition has better robustness,improves the accuracy of video portrait recognition,and expands the artificial intelligence technology for identity recognition.