Unrestricted Face Recognition Algorithm Based on Transfer Learning on Self-Pickup Cabinet

Abstract

In the contactless delivery scenario, the self-pickup cabinet is an important terminal delivery device, and face recognition is one of the efficient ways to achieve contactless access express delivery. In order to effectively recognize face images under unrestricted environments, an unrestricted face recognition algorithm based on transfer learning is proposed in this study. First, the region extraction network of the faster RCNN algorithm is improved to improve the recognition speed of the algorithm. Then, the first transfer learning is applied between the large ImageNet dataset and the face image dataset under restricted conditions. The second transfer learning is applied between face image under restricted conditions and unrestricted face image datasets. Finally, the unrestricted face image is processed by the image enhancement algorithm to increase its similarity with the restricted face image, so that the second transfer learning can be carried out effectively. Experimental results show that the proposed algorithm has better recognition rate and recognition speed on the CASIA-WebFace dataset, FLW dataset, and MegaFace dataset.

An optimal takeout supply system of intelligent self-pickup cabinets: Evidence from campus safety during COVID-19 in China

“…Recently, due to the practical significance and development prospects of the ISPCs, Xiao et al (2017) built a location model of self-pickup cabinets based on progressive service radius with maximum coverage and optimal benefit, in which service satisfaction depends on service distance. Based on transfer learning under unrestricted environments, Liang (2021) developed an unrestricted face recognition algorithm to intellectualizing selfpickup cabinets. In order to solve the location-allocation problem of self-pickup points under multiple types of demand at the express end, Li & Mao (2021) constructed a mixed integer programming model to minimize the total cost of express delivery enterprises, which provided a model basis for the location decision of various types of self-pickup cabinets and the allocation decision of each demand point.…”