Unmanned aerial vehicles (UAVs)-based Person Re-Identification (ReID) is a novel field. Person ReID is the task of identifying individuals across different frames or views, often in surveillance or security contexts. At the same time, UAVs enhance pe...
With the development of human society, there is an increasing importance for reliable person identification and authentication to protect a person’s material and intellectual property. Person identification based on brain signals has captured s...
The deployment of unmanned aerial vehicles (i.e., drones) in military and police operations implies that drones can provide footage that is of sufficient quality to enable the recognition of strategic targets, criminal suspects, and missing persons....
Cross-domain person re-identification is a technique for identifying the same individual across different cameras or environments that necessitates the overcoming of challenges posed by scene variations, which is a primary challenge in person re-iden...
With the development of ultra-long-range visual sensors, the application of unsupervised person re-identification algorithms to them has become increasingly important. However, these algorithms inevitably generate noisy pseudo-labels, which seriously...
Person re-identification (ReID) plays an important role in intelligent surveillance and receives widespread attention from academics and the industry. Due to extreme changes in viewing angles, some discriminative local regions are suppressed. In addi...
Person re-identification (Re-ID) plays an important role in the search for missing people and the tracking of suspects. Person re-identification based on deep learning has made great progress in recent years, and the application of the pedestrian con...
Person re-identification (Re-ID) aims to retrieve a particular pedestrian’s identification from a surveillance system consisting of non-overlapping cameras. In recent years, researchers have begun to focus on open-world person Re-ID tasks based...
Person re-identification in the image processing domain has been a challenging research topic due to the influence of pedestrian posture, background, lighting, and other factors. In this paper, the method of harsh learning is applied in person re-ide...
Humans always identify persons through their characteristics, salient attributes, and these attributes’ locations on the body. Most person re-identification methods focus on global and local features corresponding to the former two discriminati...
With the advancement in pose estimation techniques, skeleton-based person identification has recently received considerable attention in many applications. In this study, a skeleton-based person identification method using a deep neural network (DNN)...
Person re-identification is the technique of identifying the same person in different camera shots, known as ReID for short. Most existing models focus on single-modality person re-identification involving only visible images. However, the visible mo...
The idea of the person re-identification (Re-ID) task is to find the person depicted in the query image among other images obtained from different cameras. Algorithms solving this task have important practical applications, such as illegal action pre...
Person re-identification is a challenging task due to the lack of person image information in occluded scenarios. The current methods for person re-identification only take into account global information, neglect local information, and are not respo...
In the upcoming 6G era, edge artificial intelligence (AI), as a key technology, will be able to deliver AI processes anytime and anywhere by the deploying of AI models on edge devices. As a hot issue in public safety, person re-identification (Re-ID)...
Person re-identification (re-ID) is a fundamental problem in the field of computer vision. The performance of deep learning-based person re-ID models suffers from a lack of training data. In this work, we introduce a novel image-specific data augment...
Person re-identification is a typical computer vision problem which aims at matching pedestrians across disjoint camera views. It is challenging due to the misalignment of body parts caused by pose variations, background clutter, detection errors, ca...
Person re-identification is concerned with matching people across disjointed camera views at different places and different time instants. This task results of great interest in computer vision, especially in video surveillance applications where the...
This study presents a trajectory-based person re-identification algorithm, embedded in a tool to detect and track customers present in a large retail store, in a multi-camera environment. The customer trajectory data are obtained from video surveilla...
Person re-identification (Re-ID) has attracted attention due to its wide range of applications. Most recent studies have focused on the extraction of deep features, while ignoring color features that can remain stable, even for illumination variation...
Person Re-Identification is an essential task in computer vision, particularly in surveillance applications. The aim is to identify a person based on an input image from surveillance photographs in various scenarios. Most Person re-ID techniques util...
Video-based person re-identification (re-identification) remains underused in real-world deployments, despite impressive benchmark performance. Most existing models rely on superficial correlations—such as clothing, background, or lighting&mdas...
Extracting fine-grained features from person images has proven crucial in person re-identification (re-ID). Although the research of convolutional neural networks (CNN) has been very successful in person re-ID, due to the small receptive field and do...
In the critical setting of a trauma team activation, team composition is crucial information that should be accessible at a glance. This calls for a technological solution, which are widely available, that allows access to the whereabouts of personne...
This research proposes constructing a network used for person re-identification called MGNACP (Multiple Granularity Network with Attention Mechanisms and Combination Poolings). Based on the MGN (Multiple Granularity Network) that combines global and...
In the present study, we developed a person re-identification network called the Multiple Granularity Attention Cosine Network (MGAC). MGAC utilizes the Multiple Granularity Network (MGN), which combines global and local features and constructs an at...
Knowing who is where is a common task for many computer vision applications. Most of the literature focuses on one of two approaches: determining who a detected person is (appearance-based re-identification) and collating positions into a list, or de...
It is challenging for a mobile robot to follow a specific target person in a dynamic environment, comprising people wearing similar-colored clothes and having the same or similar height. This study describes a novel framework for a person identificat...
Existing person re-identification methods utilizing CLIP (Contrastive Language-Image Pre-training) mostly suffer from coarse-grained alignment issues. This is primarily due to the original design intention of the CLIP model, which aims at broad and g...
Person re-identification has become an essential application within computer vision due to its ability to match the same person over non-overlapping cameras. However, it is a challenging task because of the broad view of cameras with a large number o...
Person re-identification is the task of matching pedestrian images across a network of non-overlapping camera views. It poses aggregated challenges resulted from random human pose, clutter from the background, illumination variations, and other facto...
Most existing person re-identification methods focus on matching still person images across non-overlapping camera views. Despite their excellent performance in some circumstances, these methods still suffer from occlusion and the changes of pose, vi...
Person re-identification (ReID) is the problem of cross-camera target retrieval. The extraction of robust and discriminant features is the key factor in realizing the correct correlation of targets. A model based on convolutional neural networks (CNN...
In person re-identification, extracting image features is an important step when retrieving pedestrian images. Most of the current methods only extract global features or local features of pedestrian images. Some inconspicuous details are easily igno...
Person identification is a critical task in applications such as security and surveillance, requiring reliable systems that perform robustly under diverse conditions. This study evaluates the Vision Transformer (ViT) and ResNet34 models across three...
Most supervised person re-identification methods show their excellent performance, but using labeled datasets is very expensive, which limits its application in practical scenarios. To solve the scalability problem, we propose a Cross-camera Erased F...
Due to the absence of tailored designs that address challenges such as variations in scale, disparities in illumination, and instances of occlusion, the implementation of current person re-identification techniques remains challenging in practical ap...
Person re-identification (re-ID) aims to retrieve images of a given individual from different camera views. Obstacles obstructing parts of a pedestrian’s body often result in incomplete identity information, impairing recognition performance. T...
The identification of a person from gait images is generally sensitive to appearance changes, such as variations of clothes and belongings. One possibility to deal with this problem is to collect possible subjects’ appearance changes in a database. H...
Person re-identification (ReID) plays a crucial role in video surveillance with the aim to search a specific person across disjoint cameras, and it has progressed notably in recent years. However, visible cameras may not be able to record enough info...
Solving the person re-identification problem involves making associations between the same person’s appearances across disjoint camera views. Further, those associations have to be made on multiple surveillance cameras in order to obtain a more...
Visible-infrared person re-identification aims to solve the matching problem between cross-camera and cross-modal person images. Existing methods strive to perform better cross-modal alignment, but often neglect the critical importance of feature enh...
In this paper, we propose a new person re-identification scheme that uses dual pyramids to construct and utilize the local multiscale feature embedding that reflects different sizes and shapes of visual feature elements appearing in various areas of...
The visible-infrared person re-identification (VI-ReID) task aims to retrieve the same pedestrian between visible and infrared images. VI-ReID is a challenging task due to the huge modality discrepancy and complex intra-modality variations. Existing...
Person re-identification (ReID) plays a significant role in video surveillance analysis. In the real world, due to illumination, occlusion, and deformation, pedestrian features extraction is the key to person ReID. Considering the shortcomings of exi...
The person re-identification (re-ID) problem has attracted growing interest in the computer vision community. Most public re-ID datasets are captured by multiple non-overlapping cameras, and the same person may appear dissimilar in different camera v...
Person re-identification (Re-ID) is a non-overlapping multi-camera retrieval task to match different images of the same person, and it has become a hot research topic in many fields, such as surveillance security, criminal investigation, and video an...
Person re-identification (re-ID) technology has attracted extensive interests in critical applications of daily lives, such as autonomous surveillance systems and intelligent control. However, light-weight and efficient person re-ID solutions are rar...
Person re-identification (ReID) is gaining more attention due to its important applications in pedestrian tracking and security prevention. Recently developed part-based methods have proven beneficial for stronger and explicit feature descriptions, b...
Person re-identification can identify specific pedestrians across cameras and solve the visual limitations of a single fixed camera scene. It achieves trajectory analysis of target pedestrians, facilitating case analysis by public security personnel....
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