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Pedestrians

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

Computational intelligence and neuroscience
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...

Crash test-based assessment of injury risks for adults and children when colliding with personal mobility devices and service robots.

Scientific reports
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 ...

Enhancing Detection Quality Rate with a Combined HOG and CNN for Real-Time Multiple Object Tracking across Non-Overlapping Multiple Cameras.

Sensors (Basel, Switzerland)
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...

A Hybrid Deep Learning and Visualization Framework for Pushing Behavior Detection in Pedestrian Dynamics.

Sensors (Basel, Switzerland)
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...

Deep Learning Methods for Speed Estimation of Bipedal Motion from Wearable IMU Sensors.

Sensors (Basel, Switzerland)
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...

Pedestrian and Animal Recognition Using Doppler Radar Signature and Deep Learning.

Sensors (Basel, Switzerland)
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,...

Integration of Multi-Head Self-Attention and Convolution for Person Re-Identification.

Sensors (Basel, Switzerland)
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...

Practical and Accurate Indoor Localization System Using Deep Learning.

Sensors (Basel, Switzerland)
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...

Identification and Improvement of Hazard Scenarios in Non-Motorized Transportation Using Multiple Deep Learning and Street View Images.

International journal of environmental research and public health
In the prioritized vehicle traffic environment, motorized transportation has been obtaining more spatial and economic resources, posing potential threats to the travel quality and life safety of non-motorized transportation participants. It is becomi...

A Preliminary Study of Deep Learning Sensor Fusion for Pedestrian Detection.

Sensors (Basel, Switzerland)
Most pedestrian detection methods focus on bounding boxes based on fusing RGB with lidar. These methods do not relate to how the human eye perceives objects in the real world. Furthermore, lidar and vision can have difficulty detecting pedestrians in...