There are 0 repository under pedestrians topic.
Code for "Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction" CVPR 2020
The easiest way to count pedestrians, cyclists, and vehicles on edge computing devices or live video feeds.
PyTorch code for ICPR 2020 paper "DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting"
Hungarian algorithm + Kalman filter multitarget (multi-object) tracker implementation.
Python tools for working with PedX dataset.
The Arrogance of Space Mapping Tool
Yet Another attempt to build a traffic system in Unity.
This project uses Histogram of Oriented Gradients for pedestrian detection and Kalman Filter for tracking and prediction
AI car & pedestrian tracking in python utilizing computer vision
A geospatial dataset focusing on walkability and pedestrian access
Pre-print version of "Assessment of Reward Functions in Reinforcement Learning for Multi-Modal Urban Traffic Control under Real-World limitations"
Haar cascade for detecting vehicles and pedestrians in videos using Python
Analysis of when and where New York City (NYC) vehicle collisions occur with a focus on collisions involving pedestrians and cyclists.
An AI based system that do detects the cars and the pedestrians from a captured video.
deployableFiles from the simulation
safety-data - react client
This repository provides the implementation of our paper "Exploring the Potential of Synthetic Data for Pedestrian Analysis" delivered for the "Computer Vision and Cognitive System" course @UNIMORE
This repository contains a real-time pedestrian detection and tracking system implemented using deep learning techniques, specifically leveraging the YOLO (You Only Look Once) V8 architecture. The system is designed to detect and track pedestrians in low-light conditions, making it suitable for applications such as night-time driving scenarios.
Smart IoT system for managing people congestion in delimited spaces.
Results from 2014 Newport pedestrian safety survey conducted by the Bicycle and Pedestrian Advisory Commission
Social Distancing Alert System