Pedestrian detection has recently attracted widespread attention as a challenging problem in computer vision. The accuracy of pedestrian detection is affected by differences in gestures, background clutter, local occlusion, differences in scales, pix...
Community is the foundation of modern cities, where urban residents spend most of their lifetime. Effective and healthy community design plays a vital role in improving residents’ living quality. Pedestrian network is an indispensable element i...
This study evaluates pedestrian continuity in Panama City, analyzing disruptions and the spatial relationship between crossings and transit stations. Using GIS and field validation, pedestrian networks were assessed based on their continuity, defined...
Pedestrian fatalities and injuries most likely occur in vehicle-pedestrian crashes. Meanwhile, engineers have tried to reduce the problems by developing a pedestrian detection function in Advanced Driver-Assistance Systems (ADAS) and autonomous vehic...
In cities today, the digitalization of mobility is one of the most crucial tools that link each single mobility service providers (e.g., ride sharing, public transportation, air travel, etc.) to users. Based on the smart pedestrian network model, the...
Pedestrian detection is a crucial task in many vision-based applications, such as video surveillance, human activity analysis and autonomous driving. Recently, most of the existing pedestrian detection frameworks only focus on the detection accuracy...
Pedestrian attribute recognition is to predict a set of attribute labels of the pedestrian from surveillance scenarios, which is a very challenging task for computer vision due to poor image quality, continual appearance variations, as well as divers...
Pedestrian trajectory prediction poses significant challenges for autonomous systems due to the intricate nature of social interactions in densely populated environments. While the existing methods frequently encounter difficulties in effectively qua...
Open public places, such as pedestrian streets, parks, and squares, are vulnerable when the pedestrians thronged into the sidewalks. The crowd count changes dynamically over time with various external factors, such as surroundings, weekends, and peak...
With the unparalleled growth of motor vehicles, traffic accident between pedestrians and vehicles is one of the most serious issues in the word-wild. Plenty of injuries and fatalities are caused by the traffic accidents and crashes. The connected veh...
Pedestrian attributes (such as gender, age, hairstyle, and clothing) can effectively represent the appearance of pedestrians. These are high-level semantic features that are robust to illumination, deformation, etc. Therefore, they can be widely used...
Pedestrian evacuation is an important measure to ensure disaster safety in central retail districts, the efficiency of which is affected by the synergy of road network planning indices. This paper established the typical forms of central retail distr...
This paper presents an extended model for a pedestrian attribute recognition network utilizing skeleton data as a soft attention model to extract a local feature corresponding to a specific attribute. This technique helped keep valuable information s...
Urban plans for pedestrian-friendly environments by reducing exposure to air pollutants and enhancing movement are crucial for public health and accessibility of social infrastructure. Here, we develop a novel network analysis-based approach, which i...
Demand for a Pedestrian Navigation Service (PNS) is on the rise. To provide a PNS for the transportation of vulnerable people, more detailed information of pedestrian facilities and obstructions should be included in Pedestrian Network Data (PND) use...
Gait recognition is a noncontact biometric procedure that determines the identity or health status of a person by analyzing his or her walking posture and habits, including skeletal and joint movements. The most remarkable feature of this method is t...
Urban high-density development has led to the emergence of complex three-dimensional pedestrian networks. As a crucial component of city centers, these networks significantly influence the spatial distribution of service industries. Understanding the...
Pedestrian flow statistics and analysis in public places is an important means to ensure urban safety. However, in recent years, a video-based pedestrian flow statistics algorithm mainly relies on binocular vision or a vertical downward camera, which...
As society evolves and technology advances, increasing transportation demands have heightened safety risks near schools and on mixed-traffic roads. While traditional studies on pedestrian evasive behavior have mainly focused on general traffic enviro...
In complex traffic environments such as low light, strong glare, occlusion and at night, systems that rely solely on visible light single sensors for pedestrian detection have drawbacks such as low detection accuracy and poor robustness. Based on the...
Due to the complexity of outdoor environments, we still face challenges in collecting up-to-date outdoor road network maps because of high data collection costs, resulting in a lack of navigation road network maps in outdoor scenarios. Existing road...
Articulation modeling, feature extraction, and classification are the important components of pedestrian segmentation. Usually, these components are modeled independently from each other and then combined in a sequential way. However, this approach i...
In traffic scenes, pedestrian target detection faces significant issues of misdetection and omission due to factors such as crowd density and obstacle occlusion. To address these challenges and enhance detection accuracy, we propose an improved CCW-Y...
Occlusion presents a major obstacle in the development of pedestrian detection technologies utilizing computer vision. This challenge includes both inter-class occlusion caused by environmental objects obscuring pedestrians, and intra-class occlusion...
Pedestrian detection has been widely used in applications such as video surveillance and intelligent robots. Recently, deep learning-based pedestrian detection engines have attracted lots of attention. However, the computational complexity of these e...
A macro network loading model for multi-flow lines, time varying, and pedestrian congestion is proposed. The station hub is abstracted as a network of different types of nodes, and the flow of passengers at each node is calculated in real time for th...
Pedestrian-related accidents are much more likely to occur during nighttime when visible (VI) cameras are much less effective. Unlike VI cameras, infrared (IR) cameras can work in total darkness. However, IR images have several drawbacks, such as low...
24 May 2019
Research has sufficiently documented the built environment correlates of walking. However, evidence is limited in investigating the comparative associations of micro- (streetscape features) and macro-level (street network design and land-use) environ...
Pedestrian detection is a challenging task, mainly owing to the numerous appearances of human bodies. Modern detectors extract representative features via the deep neural network; however, they usually require a large training set and high-performanc...
Predominantly, dense historical cities face insufficient pedestrian-level greenery in the urban spaces. The lack of greenery impacts the human thermal comfort on the walking paths, which contributes to a considerable reduction in pedestrian flow rate...
Statistical mechanics of walks defined on the spatial graphs of the city of Lubbock (10,421 nodes) and the Texas Tech University (TTU) campus pedestrian network (1466 nodes) are used for evaluating structural isolation and the integration of graph no...
A number of studies have been conducted to enhance the pedestrian detection accuracy of intelligent surveillance systems. However, detecting pedestrians under outdoor conditions is a challenging problem due to the varying lighting, shadows, and occlu...
Walking is the original form of transportation, and pedestrians have always made up a significant share of transportation system users. In contrast to motorized traffic, which has to move on precisely defined lanes and follow strict rules, pedestrian...
Identifying the factors that control the dynamics of pedestrians is a crucial step towards modeling and building various pedestrian-oriented simulation systems. In this article, we empirically explore the influential factors that control the single-f...
Walking is the primary mode of reaching metro stations, yet the quality of pedestrian networks around these stations has not been well researched. Considering the objective physical characteristics of pedestrian networks and the subjective assessment...
Nowadays, pedestrian detection is widely used in fields such as driving assistance and video surveillance with the progression of technology. However, although the research of single-modal visible pedestrian detection has been very mature, it is stil...
Pedestrian safety is alarming worldwide, and it is well validated that distracted walking/crossing involving mobile phone use would significantly compromise pedestrian safety. Some existing studies demonstrated that distracted pedestrians would spend...
The research presented in this paper studied interrelationships within the perceptions of pedestrian and cyclist environments, travel behaviors, and a particular subset of social networks characterized by their being usual trip or activity companions...
Predicting pedestrian trajectories in urban scenarios is a challenging task that has a wide range of applications, from video surveillance to autonomous driving. The task is difficult since pedestrian behavior is affected by both their individual pat...
In recent years, the application of artificial intelligence (AI) in the automotive industry has led to the development of intelligent systems focused on road safety, aiming to improve protection for drivers and pedestrians worldwide to reduce the num...
Evidence for the benefits of walking has attracted the attention of researchers and practitioners and encouraged them to develop healthier and more sustainable walkable cities. Many methods and approaches have been developed to measure walkability; n...
Pedestrian trajectory prediction is one of the most important topics to be researched for unmanned driving and intelligent mobile robots to perform perceptual interaction with the environment. To solve the problem of the SGAN (social generative adver...
Limited research from the Global South has examined pedestrian accessibility to key destinations, particularly while considering efficient and practical sidewalk-specific conditions. This study employs a case-based approach, scrutinising walking acce...
Advanced object detection methods always face high algorithmic complexity or low accuracy when used in pedestrian target detection for the autonomous driving system. This paper proposes a lightweight pedestrian detection approach called the YOLOv5s-
This paper proposes a margin CosReid network for effective pedestrian re-identification. Aiming to overcome the overfitting, gradient explosion, and loss function non-convergence problems caused by traditional CNNs, the proposed GBNeck model can real...
Serious scale variation is a key challenge in pedestrian detection. Most works typically employ a feature pyramid network to detect objects at diverse scales. Such a method suffers from information loss during channel unification. Inadequate sampling...
The 15-min neighborhood paradigm has reshaped the evaluation system of urban pedestrian mobility, shifting pedestrian network assessment from single facility supply to holistic topological structural analysis. Structural fracture of pedestrian system...
Pedestrian detection is a crucial task in computer vision, with various applications in surveillance, autonomous driving, and robotics. However, detecting pedestrians in complex scenarios, such as rainy days, remains a challenging problem due to the...
Analysis of pedestrians’ motion is important to real-world applications in public scenes. Due to the complex temporal and spatial factors, trajectory prediction is a challenging task. With the development of attention mechanism recently, transf...
As an important part of autonomous driving intelligence perception, pedestrian detection has high requirements for parameter size, real-time, and model performance. Firstly, a novel multiplexed connection residual block is proposed to construct the l...
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