Abstract

Abstract. Person re-identification (ReID) in color and thermal images require matching of the object color and its temperature. While thermal cameras increase the performance of ReID systems during the night-time, identification of corresponding features in the visible and the long-wave infrared range is challenging. The biggest challenge arises from the multimodal relationship between an object’s color and its temperature. Modern ReID methods provide state-of-the-art results in person matching in the visible range. Hence, it is possible to perform multimodal matching by translation of a thermal probe image to the color domain. After that, the synthetic color probe image is matched with images from the real color gallery set. This paper is focused on the development of the ThermalReID multispectral person ReID framework. The framework performs matching in two steps. Firstly, it colorizes the input thermal probe image using a Generative Adversarial Network (GAN). Secondly, it matches images in the color domain using color histograms and MSCR features. We evaluate the ThermalReID framework using RegDB and ThermalWorld datasets. The results of the evaluation are twofold. Firstly, the developed GAN performs realistic colorization of thermal images. Secondly, the ThermalReID framework provides matching of persons in color and thermal images that compete with and surpass the state-of-the-art. The developed ThermalReID framework can be used in video surveillance systems for effective person ReID during the nighttime.

Highlights

  • Person Re-identification (ReID) is the problem of matching of the same humans captured in different images

  • This paper is focused on the development of a cross-modality person ReID framework ThermalReID

  • We present three key technical contributions: 1. ColorMatchGAN model for colorization of a long-wave infrared image using a ‘hint’ color image

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Summary

Introduction

Person Re-identification (ReID) is the problem of matching of the same humans captured in different images. The images can be captured using different cameras and during a different time. The only requirement is that the appearance (clothes, shoes, etc.) of a person remains unchanged across all the images. The ReID system for a given image Ip(i, j) showing a person j from a camera i should find a set of images s = {I1, I2, . . .} from other cameras, where the person P is visible. Person ReID problem received a lot of scholar attention recently (Farenzena et al, 2010, Bhuiyan et al, 2015, Bhuiyan et al, 2018). A robust cross-domain feature matching is required for identification of the same person in a different spectral range

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