The study aims to explore a method for identifying corresponding objects across multiple camera views, to improve the accuracy of object re-identification. We analyzed various techniques, including contour detection, region of interest extraction, and keypoint extraction. We also examined the challenges of finding object correspondences between multiple camera views. To evaluate the effectiveness of the proposed method, we utilized two human attribute datasets, Market-1501 and DukeMTMC-reID, and performed extensive testing on these datasets.
This work is aimed at generalizing the methods of laser polarimetry in the case of partially depolarizing optically anisotropic methyl acrylate layers. A method of differential Mueller-matrix mapping is proposed and substantiated for reproducing the distributions of the parameters of linear and circular birefringence and dichroism of partially depolarizing methyl acrylate layers.
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