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Image feature extraction method for person re-identification

机译:图像特征提取方法对人重新识别

摘要

An image feature extraction method for person re-identification includes performing person re-identification by means of aligned local descriptor extraction and graded global feature extraction; performing the aligned local descriptor extraction by processing an original image by affine transformation and performing a summation pooling operation on image block features of same regions to obtain an aligned local descriptor; reserving spatial information between inner blocks of the image for the aligned local descriptor; and performing the graded global feature extraction by grading a positioned pedestrian region block and solving a corresponding feature mean value to obtain a global feature. The method can resolve the problem of feature misalignment caused by posture changes of pedestrian, etc., and eliminate the effect of unrelated backgrounds on re-recognition, thus improving the precision and robustness of person re-identification.
机译:用于人重新识别的图像特征提取方法包括通过对准的本地描述符提取和分级全局特征提取来执行人重新识别; 通过通过仿射变换处理原始图像并对同一区域的图像块特征执行求和汇总操作来执行对齐的本地描述符提取,以获得对齐的本地描述符; 为对齐的本地描述符保留图像内部块之间的空间信息; 通过分级定位的行人区域块来执行分级全局特征提取,并解决相应的特征均值以获得全局特征。 该方法可以解决由行人等姿势变化引起的特征未对准的问题,并消除无关背景对重新识别的影响,从而提高人员重新识别的精度和鲁棒性。

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