Advanced Pedestrian State Sensing Method for Automated Patrol Vehicle Based on Multi-Sensor Fusion
Sensors, 2022 At present, the COVID-19 pandemic still presents with outbreaks occasionally, and pedestrians in public areas are at risk of being infected by the viruses.
Pangwei Wang +3 more
doaj +1 more source
DMPNet: densely connected multi-scale pyramid networks for crowd counting [PDF]
PeerJ Computer Science, 2022 Crowd counting has been widely studied by deep learning in recent years. However, due to scale variation caused by perspective distortion, crowd counting is still a challenging task.
Pengfei Li +3 more
doaj +2 more sources
Analysis-by-synthesis: Pedestrian tracking with crowd simulation models in a multi-camera video network [PDF]
, 2015 For tracking systems consisting of multiple cameras with overlapping field-of-views, homography-based approaches are widely adopted to significantly reduce occlusions among pedestrians by sharing information among multiple views.
Bhanu, B, Jin, Z
core +1 more source
Improved Crowd Counting Method Based on Scale-Adaptive Convolutional Neural Network
IEEE Access, 2019 Crowd counting is a challenging task due to the influence of various factors, such as scene transformation, complex crowd distribution, uneven illumination, and occlusion.
Jun Sang +6 more
doaj +1 more source
Context-Aware Multi-Scale Aggregation Network for Congested Crowd Counting
Sensors, 2022 In this paper, we propose a context-aware multi-scale aggregation network named CMSNet for dense crowd counting, which effectively uses contextual information and multi-scale information to conduct crowd density estimation.
Liangjun Huang +4 more
doaj +1 more source
Cascaded Multi-Task Learning of Head Segmentation and Density Regression for RGBD Crowd Counting
IEEE Access, 2020 In this paper we propose a novel regression based RGBD crowd counting method. Compared with previous RGBD crowd counting methods which mainly exploit depth cue to facilitate person/head detection, our approach adopts density map regression and is more ...
Desen Zhou, Qian He
doaj +1 more source
DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation
, 2018 In real-world crowd counting applications, the crowd densities vary greatly in spatial and temporal domains. A detection based counting method will estimate crowds accurately in low density scenes, while its reliability in congested areas is downgraded ...
Gao, Chenqiang +3 more
core +1 more source
Geometric and Physical Constraints for Drone-Based Head Plane Crowd Density Estimation
, 2019 State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density in the image plane. While useful for this purpose, this image-plane density has no immediate physical meaning because it is subject to ...
Fua, Pascal +3 more
core +1 more source
Detection of High-Density Crowds in Aerial Images Using Texture Classification
Remote Sensing, 2016 Automatic crowd detection in aerial images is certainly a useful source of information to prevent crowd disasters in large complex scenarios of mass events.
Oliver Meynberg +2 more
doaj +1 more source
MH-MetroNet—A Multi-Head CNN for Passenger-Crowd Attendance Estimation
Journal of Imaging, 2020 Knowing an accurate passengers attendance estimation on each metro car contributes to the safely coordination and sorting the crowd-passenger in each metro station.
Pier Luigi Mazzeo +6 more
doaj +1 more source