AIMC Topic: Pedestrians

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Research on Athlete Detection Method Based on Visual Image and Artificial Intelligence System.

Computational intelligence and neuroscience Sep 29, 2022
Pedestrian detection and tracking based on computer vision has gradually become an international pattern recognition, which is one of the most active research topics in the field of computer vision and artificial intelligence. Using the theoretical r...
Pedestrians Artificial Intelligence Motion Athletes Algorithms Humans
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Practical and Accurate Indoor Localization System Using Deep Learning.

Sensors (Basel, Switzerland) Sep 7, 2022
Indoor localization is an important technology for providing various location-based services to smartphones. Among the various indoor localization technologies, pedestrian dead reckoning using inertial measurement units is a simple and highly practic...
Walking Humans Pedestrians Algorithms Deep Learning Smartphone
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Integration of Multi-Head Self-Attention and Convolution for Person Re-Identification.

Sensors (Basel, Switzerland) Aug 21, 2022
Person re-identification is essential to intelligent video analytics, whose results affect downstream tasks such as behavior and event analysis. However, most existing models only consider the accuracy, rather than the computational complexity, which...
Pedestrians Pattern Recognition, Automated Humans Neural Networks, Computer Learning
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A Hybrid Deep Learning and Visualization Framework for Pushing Behavior Detection in Pedestrian Dynamics.

Sensors (Basel, Switzerland) May 26, 2022
Crowded event entrances could threaten the comfort and safety of pedestrians, especially when some pedestrians push others or use gaps in crowds to gain faster access to an event. Studying and understanding pushing dynamics leads to designing and bui...
Machine Learning Algorithms Deep Learning Pedestrians Humans Neural Networks, Computer
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Deep Learning Methods for Speed Estimation of Bipedal Motion from Wearable IMU Sensors.

Sensors (Basel, Switzerland) May 19, 2022
The estimation of the speed of human motion from wearable IMU sensors is required in applications such as pedestrian dead reckoning. In this paper, we test deep learning methods for the prediction of the motion speed from raw readings of a low-cost I...
Wearable Electronic Devices Pedestrians Humans Deep Learning Motion Leg
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Pedestrian and Animal Recognition Using Doppler Radar Signature and Deep Learning.

Sensors (Basel, Switzerland) May 1, 2022
Pedestrian occurrences in images and videos must be accurately recognized in a number of applications that may improve the quality of human life. Radar can be used to identify pedestrians. When distinct portions of an object move in front of a radar,...
Humans Neural Networks, Computer Radar Pedestrians Ultrasonography, Doppler Animals Deep Learning
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Crash test-based assessment of injury risks for adults and children when colliding with personal mobility devices and service robots.

Scientific reports Mar 28, 2022
Autonomous mobility devices such as transport, cleaning, and delivery robots, hold a massive economic and social benefit. However, their deployment should not endanger bystanders, particularly vulnerable populations such as children and older adults ...
Aged Accidental Falls Child Robotics Craniocerebral Trauma Humans Pedestrians Accidents, Traffic
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Enhancing Detection Quality Rate with a Combined HOG and CNN for Real-Time Multiple Object Tracking across Non-Overlapping Multiple Cameras.

Sensors (Basel, Switzerland) Mar 9, 2022
Multi-object tracking in video surveillance is subjected to illumination variation, blurring, motion, and similarity variations during the identification process in real-world practice. The previously proposed applications have difficulties in learni...
Normal Distribution Neural Networks, Computer Algorithms Pedestrians Humans Motion
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Contextual Detection of Pedestrians and Vehicles in Orthophotography by Fusion of Deep Learning Algorithms.

Sensors (Basel, Switzerland) Feb 11, 2022
In the context of smart cities, monitoring pedestrian and vehicle movements is essential to recognize abnormal events and prevent accidents. The proposed method in this work focuses on analyzing video streams captured from a vertically installed came...
Deep Learning Cities Neural Networks, Computer Humans Algorithms Pedestrians
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Multi-Task Learning With Coarse Priors for Robust Part-Aware Person Re-Identification.

IEEE transactions on pattern analysis and machine intelligence Feb 3, 2022
Part-level representations are important for robust person re-identification (ReID), but in practice feature quality suffers due to the body part misalignment problem. In this paper, we present a robust, compact, and easy-to-use method called the Mul...
Pedestrians Algorithms Databases, Factual Deep Learning Humans
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