AIMC Topic: Pedestrians

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Feature Channel Expansion and Background Suppression as the Enhancement for Infrared Pedestrian Detection.

Sensors (Basel, Switzerland) Sep 9, 2020
Pedestrian detection is an important task in many intelligent systems, particularly driver assistance systems. Recent studies on pedestrian detection in infrared (IR) imagery have employed data-driven approaches. However, two problems in deep learnin...
Humans Algorithms Deep Learning Pedestrians Infrared Rays
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Adopting Machine Learning and Spatial Analysis Techniques for Driver Risk Assessment: Insights from a Case Study.

International journal of environmental research and public health Jul 18, 2020
Traffic violations usually caused by aggressive driving behavior are often seen as a primary contributor to traffic crashes. Violations are either caused by an unintentional or deliberate act of drivers that jeopardize the lives of fellow drivers, pe...
Pedestrians Accidents, Traffic Automobile Driving Geographic Information Systems China Spatial Analysis Humans Machine Learning Risk Assessment
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RNN-Aided Human Velocity Estimation from a Single IMU.

Sensors (Basel, Switzerland) Jun 29, 2020
Pedestrian Dead Reckoning (PDR) uses inertial measurement units (IMUs) and combines velocity and orientation estimates to determine a position. The estimation of the velocity is still challenging, as the integration of noisy acceleration and angular ...
Pedestrians Acceleration Movement Humans Neural Networks, Computer Algorithms
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Hybrid SVM-CNN Classification Technique for Human-Vehicle Targets in an Automotive LFMCW Radar.

Sensors (Basel, Switzerland) Jun 21, 2020
Human-vehicle classification is an essential component to avoiding accidents in autonomous driving. The classification technique based on the automotive radar sensor has been paid more attention by related researchers, owing to its robustness to low-...
Accidents, Traffic Radar Motor Vehicles Algorithms Support Vector Machine Pedestrians Humans Neural Networks, Computer
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Deep Learning-Based Human Activity Real-Time Recognition for Pedestrian Navigation.

Sensors (Basel, Switzerland) Apr 30, 2020
Several pedestrian navigation solutions have been proposed to date, and most of them are based on smartphones. Real-time recognition of pedestrian mode and smartphone posture is a key issue in navigation. Traditional ML (Machine Learning) classificat...
Pedestrians Human Activities Machine Learning Algorithms Deep Learning Humans Neural Networks, Computer
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Doppler-Spectrum Feature-Based Human-Vehicle Classification Scheme Using Machine Learning for an FMCW Radar Sensor.

Sensors (Basel, Switzerland) Apr 2, 2020
In this paper, we propose a Doppler-spectrum feature-based human-vehicle classification scheme for an FMCW (frequency-modulated continuous wave) radar sensor. We introduce three novel features referred to as the scattering point count, scattering poi...
Automobile Driving Ultrasonography, Doppler Radar Signal Processing, Computer-Assisted Pedestrians Humans Machine Learning Algorithms Support Vector Machine
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Pedestrian Navigation Method Based on Machine Learning and Gait Feature Assistance.

Sensors (Basel, Switzerland) Mar 10, 2020
In recent years, as the mechanical structure of humanoid robots increasingly resembles the human form, research on pedestrian navigation technology has become of great significance for the development of humanoid robot navigation systems. To solve th...
Humans Gait Neural Networks, Computer Pedestrians Machine Learning Acceleration Wearable Electronic Devices Motion Algorithms Monitoring, Ambulatory Robotics Reproducibility of Results Foot Walking Biomechanical Phenomena
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Development of pedestrian crash prediction model for a developing country using artificial neural network.

International journal of injury control and safety promotion Jul 4, 2019
Urban intersections in India constitute a significant share of pedestrian fatalities. However, model-based prediction of pedestrian fatalities is still in a nascent stage in India. This study proposes an artificial neural network (ANN) technique to d...
Accidents, Traffic Humans Bayes Theorem Neural Networks, Computer Safety Risk Factors Developing Countries Environment Design Pedestrians
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Applying machine learning approaches to analyze the vulnerable road-users' crashes at statewide traffic analysis zones.

Journal of safety research May 10, 2019
INTRODUCTION: In this paper, we present machine learning techniques to analyze pedestrian and bicycle crash by developing macro-level crash prediction models.
Pedestrians Transportation Socioeconomic Factors Humans Safety Environment Design Accidents, Traffic Motor Vehicles Machine Learning Automobile Driving Models, Statistical Bicycling
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A Dynamic Part-Attention Model for Person Re-Identification.

Sensors (Basel, Switzerland) May 5, 2019
Person re-identification (ReID) is gaining more attention due to its important applications in pedestrian tracking and security prevention. Recently developed part-based methods have proven beneficial for stronger and explicit feature descriptions, b...
Humans Neural Networks, Computer Algorithms Biometric Identification Image Processing, Computer-Assisted Pedestrians Video Recording
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