For the question regarding the relationship between personal factors and location selection, many researches support the effect of personal features for personal location favorite. However, it is also found that not all of personal factors are effect...
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...
Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture...
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...
Most existing occluded person re-identification (Re-ID) methods rely on external cues to separate the visible parts of the person from the occluded regions, aiming to achieve alignment based on visible body parts. However, such methods often overlook...
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...
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...
Human personality (HP) is seen as an individual’s consistent patterns of feeling, thinking, and behaving by today’s psychological studies, in which HPs are characterized in terms of traits—in particular, as relatively enduring chara...
Person Re-identification (Person Re-ID) is essential in surveillance and security. Traditional image processing methods often struggle to identify individuals accurately due to the sensitivity to occlusions and limited discriminative capability of th...
Existing person search methods mainly focus on searching for the target person using database images. However, this is different from real-world surveillance videos which involve a temporal relationship between video frames. To solve this problem, we...
Person re-identification(Re-ID) technology has been a research hotspot in intelligent video surveillance, which accurately retrieves specific pedestrians from massive video data. Most research focuses on the short-term scenarios of person Re-ID to de...
Occluded person re-identification (Re-ID) is a challenging task, as non-target pedestrians or surrounding obstacles often interfere with the visual cues of the target person, making it difficult for models to effectively learn discriminative feature...
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...
Over the past few years, personalized recommendation systems aim to address the problem of information overload to help users achieve useful information and make quick decisions. Recently, due to the benefits of effective representation learning and...
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...
Smart security is needed for complex scenarios such as all-weather and multi-scene environments, and visible–infrared person re-identification (VI Re-ID) has become a key technique in this field. VI Re-ID is usually modeled as a pattern recogni...
Background: Health benefits from physical activity (PA) can be achieved by following the WHO recommendation for PA. To increase PA in inactive individuals, digital interventions can provide cost-effective and low-threshold access. Moreover, gamificat...
To solve the problem of inadequate feature extraction by the model due to factors such as occlusion and illumination in person re-identification tasks, this paper proposed a model with a joint cross-consistency learning and multi-feature fusion perso...
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...
With the rapid advancement of deep learning theory and hardware device computing capacity, computer vision tasks, such as object detection and instance segmentation, have entered a revolutionary phase in recent years. As a result, extremely challengi...
Video-based person re-identification is an important task with the challenges of lighting variation, low-resolution images, background clutter, occlusion, and human appearance similarity in the multi-camera visual sensor networks. In this paper, we p...
Person re-identification (Re-ID) is a technique for identifying target pedestrians in images or videos. In recent years, owing to the advancements in deep learning, research on person re-identification has made significant progress. However, current...
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...
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...
With the explosive growth of mobile videos, helping users quickly and effectively find mobile videos of interest and further provide personalized recommendation services are the developing trends of mobile video applications. Mobile videos are charac...
Unsupervised person re-identification has attracted a lot of attention due to its strong potential to adapt to new environments without manual annotation, but learning to recognise features in disjoint camera views without annotation is still challen...
The risks associated with hazardous materials (HazMat) transportation exhibit typical characteristics of chain-like distribution, spatiotemporal regularity, and individual heterogeneity. A personalized trip-chain feature spectra recognition framework...
Due to the lack of a specific design for scenarios such as scale change, illumination difference, and occlusion, current person re-identification methods are difficult to put into practice. A Multi-Branch Feature Fusion Network (MFFNet) is proposed,...
Visible-infrared person re-identification (VIPR) has great potential for intelligent video surveillance systems at night, but it is challenging due to the huge modal gap between visible and infrared modalities. For that, this paper proposes a minimiz...
Person re-identification aims to match images of the same individual across non-overlapping cameras by analyzing personal characteristics. Recently, Transformer-based models have demonstrated excellent capabilities and achieved breakthrough progress...
Person re-identification (Re-ID) has attracted considerable attention in the field of computer vision, primarily due to its critical role in video surveillance and public security applications. However, most existing Re-ID approaches rely on image-le...
We analyzed the contribution of electroencephalogram (EEG) data, age, sex, and personality traits to emotion recognition processes—through the classification of arousal, valence, and discrete emotions labels—using feature selection techni...
The purpose of person re-identification is to identify and retrieve the same individual across different scenes, angles, and times. As an instance-level recognition problem, human re-identification relies on discriminative features, but is not determ...
In this work, we focus on the misalignment problem in person re-identification. Human body parts commonly contain discriminative local representations relevant with identity recognition. However, the representations are easily affected by misalignmen...
Artificial intelligence can help physicians improve the accuracy of breast cancer diagnosis. However, the effectiveness of AI applications is limited by doctors’ adoption of the results recommended by the personalized medical decision support system....
Cross-modal person re-identification between visible and infrared domains remains a challenging problem due to significant modality gaps. This paper presents a novel approach termed Intermediate Shared Feature Network (ISFNet) that explicitly address...
To address challenges related to the inadequate representation and inaccurate discrimination of pedestrian attributes, we propose a novel method for person re-identification, which leverages global feature learning and classification optimization. Sp...
In order to minimize the disparity between visible and infrared modalities and enhance pedestrian feature representation, a cross-modality person re-identification method is proposed, which integrates modality generation and feature enhancement. Spec...
Existing video person re-identification (ReID) methods still face three major challenges: limited spatial perception from RGB-only inputs, equal-weight local feature extraction under occlusion, and ineffective fusion of heterogeneous motion and appea...
Continuous and noninvasive blood pressure (BP) monitoring is important for hypertension screening and long-term cardiovascular management. Continuous BP estimation using photoplethysmography (PPG) and electrocardiography (ECG) has become a promising...
The human body is often occluded by a variety of obstacles in the monitoring system, so occluded person re-identification is still a long-standing challenge. Recent methods based on pose guidance or external semantic clues have improved the represent...
Person re-identification (Re-ID) aims to retrieve a specific pedestrian across a multi-disjoint camera in a surveillance system. Most of the research is based on a strong assumption that images should contain a full human torso. However, it cannot be...
Occlusion remains a major challenge in person re-identification, as it often leads to incomplete or misleading visual cues. To address this issue, we propose a dual-branch occlusion-aware network (DOAN), which explicitly and implicitly enhances the m...
Although overall colorectal cancer (CRC) incidence and mortality have declined with widespread screening, early-onset CRC (EOCRC), defined as diagnosis before age 50, continues to rise. EOCRC partially differs from late-onset CRC (LOCRC) in clinical...
Person reidentification (re-ID) has been receiving increasing attention in recent years due to its importance for both science and society. Machine learning (particularly Deep Learning (DL)) has become the main re-ID tool that has allowed to achieve...
Children in difficulty are at heightened risk of developing personality-related problems, partly due to gaps in family care and social protection. This study examines whether (a) the availability of an individual study desk at home—a basic fami...
The process of manually scoring drawings for the Goodenough–Harris Draw-a-Person (DAP) test is time-consuming and labor-intensive. It is also prone to inconsistencies due to subjective interpretation. Keeping these drawbacks in mind, this study...
This study focuses on personal identification using bidirectional long short-term memory (LSTM) with efficient features from electromyogram (EMG) biomedical signals. Personal identification is performed by comparing and analyzing features that can be...
15 February 2023
Up-to-date anthropometric data on the human population are needed for designing safe and ergonomically efficient workplaces. An important determinant of safety and ergonomic comfort at work is knowledge of the value of dimensional allowances (DAs) wh...
Although gait recognition has been greatly improved by efforts from many researchers in recent years, its performance is still unsatisfactory due to the lack of gait information under the real scenariowhere only one or two images may be used for reco...
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