Yang Dai^*, Zhiyuan Luo

Journal of New Media, Vol.3, No.4, pp. 129-136, 2021, DOI:10.32604/jnm.2021.023981 - 05 November 2021

Abstract Person re-identification (re-ID) aims to match images of the same pedestrian across different cameras. It plays an important role in the field of security and surveillance. Although it has been studied for many years, it is still considered as an unsolved problem. Since the rise of deep learning, the accuracy of supervised person re-ID on public datasets has reached the highest level. However, these methods are difficult to apply to real-life scenarios because a large number of labeled training data is required in this situation. Pedestrian identity labeling, especially cross-camera pedestrian identity labeling, is heavy More >

Yong Li, Xipeng Wang^*

Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 563-573, 2021, DOI:10.32604/iasc.2021.017926 - 11 August 2021

Abstract Person re-identification (ReID) is the use of computer vision and machine learning techniques to determine whether the pedestrians in the two images under different cameras are the same person. It can also be regarded as a matching retrieval task for person targets in different scenes. The research focuses on how to obtain effective person features from images with occlusion, angle change, and target attitude change. Based on the present difficulties and challenges in ReID, the paper proposes a ReID method based on joint loss and multi-attention network. It improves the person re-identification algorithm based on More >

Zhiyuan Luo^*

Journal of New Media, Vol.3, No.1, pp. 11-17, 2021, DOI:10.32604/jnm.2021.018027 - 15 March 2021

Abstract Person re-ID is becoming increasingly popular in the field of modern surveillance. The purpose of person re-ID is to retrieve person of interests in non-overlapping multi-camera surveillance system. Due to the complexity of the surveillance scene, the person images captured by cameras often have problems such as size variation, rotation, occlusion, illumination difference, etc., which brings great challenges to the study of person re-ID. In recent years, studies based on deep learning have achieved great success in person re-ID. The improvement of basic networks and a large number of studies on the influencing factors have More >

Junchuan Yang^*

Journal of New Media, Vol.2, No.4, pp. 137-148, 2020, DOI:10.32604/jnm.2020.014278 - 23 December 2020

Abstract Person Re-identification (re-ID) is a hot research topic in the field of computer vision now, which can be regarded as a sub-problem of image retrieval. The goal of person re-ID is to give a monitoring pedestrian image and retrieve other images of the pedestrian across the device. At present, person re-ID is mainly divided into two categories. One is the traditional methods, which relies heavily on manual features. The other is to use deep learning technology to solve. Because traditional methods mainly rely on manual feature, they cannot adapt well to a complex environment with More >

Tong Jiang^*

Journal of New Media, Vol.2, No.2, pp. 45-60, 2020, DOI:10.32604/jnm.2020.09823 - 21 August 2020

Abstract Recently, person Re-identification (person Re-id) has attracted more and more attention, which has become a research focus of computer vision community. Person Re-id is used to ascertain whether the target pedestrians captured by cameras in different positions at different moments are the same person or not. However, due to the influence of various complex factors, person Re-id still has a lot of holes to be filled. In this paper, we first review the research process of person Re-id, and then, two kinds of mainstream methods for person Re-id are introduced respectively, according to the different More >