关键词: 图像检索, HOG 算法, 残差网络, 分类模型

Abstract: For public safety video image information trajectory tracking problem，a fast video content retrieval system based on image recognition is designed． The HOG( Oriented Histogram Feature Extraction) algorithm is used for face location，and the ＲesNet model is re-trained through migration learning to establish a dedicated Neural network classifier． The process of retrieving video content is to extract the key frames of the video，locate the characters therein，extract the feature values，and use the trained classification model for classifying． The classification information is marked on the picture，the relevant information is stored in the database，and the database is queried for detailed information． Experimental results show that the system can effectively locate the information of the video and accurately capture the image． In the field of public security，it has application prospects．

Key words: search image, oriented histogram feature extraction ( HOG ) algorithm, residual network, classification model