There are 11 repositories under vehicle-detection-and-tracking topic.
:oncoming_automobile: "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
A collection of all projects pertaining to different layers in the SDC software stack
The main objective of this project is to identify overspeed vehicles, using Deep Learning and Machine Learning Algorithms. After acquisition of series of images from the video, trucks are detected using Haar Cascade Classifier. The model for the classifier is trained using lots of positive and negative images to make an XML file. This is followed by tracking down the vehicles and estimating their speeds with the help of their respective locations, ppm (pixels per meter) and fps (frames per second). Now, the cropped images of the identified trucks are sent for License Plate detection. The CCA (Connected Component Analysis) assists in Number Plate detection and Characters Segmentation. The SVC model is trained using characters images (20X20) and to increase the accuracy, 4 cross fold validation (Machine Learning) is also done. This model aids in recognizing the segmented characters. After recognition, the calculated speed of the trucks is fed into an excel sheet along with their license plate numbers. These trucks are also assigned some IDs to generate a systematized database.
Vehicle detection, tracking and counting by SVM is trained with HOG features using OpenCV on c++.
Detecting Cars in real time and identifying the speed of cars and tracking
Automatic detection and tracking of moving vehicles in a video from a surveillance camera
detect the no of people every second entering building gate. #person-detection
Detecting Cars in real time and identifying the speed of cars and tracking
Modified TensorFlow Object Detection Model for vehicle detection and tracking
Zero-VIRUS: Zero-shot VehIcle Route Understanding System for Intelligent Transportation (CVPR 2020 AI City Challenge Track 1)
A deep learning and computer vision based warning indicator system for the vehicle drivers using live dash-cam footage.
Vehicle Tracking Full Project Using C#,ASP.net,Javascript etc
Term 1, Project 5 - Udacity Self Driving Car Nanodegree
Vehicle detection, tracking, counting and speed prediction on videos with OpenCV.
Video/Image processing project using Blob Detection.
Combined lane and vehicle detection pipeline comparing YOLOv2 and LeNet-5
Proyecto de control de trafico e intercepción de semáforos inteligentes.
Semi-automatic detection, tracking and labelling of active targets for autonomous driving.
Track a single car by using Kalman filter
Udacity Self-Driving Car Nanodegree: Vehicle Detection Project
detect objects from cctv camera
Predict the trajectory of the vehicles in HCM city streets with YOLOv7 + DeepSORT + CNN-LSTM/CNN-GRU.
Traffic survey automator is a software that analyses traffic recordings using deep learning and statistical algorithms. It outputs the numbers of vehicles passing through the defined regions of interest.
Vehicle Re-Identification (ReID) dataset contains over 55,000 images for training and validation of the vehicle re-identification model
Vehicle Detection Project
Project5 - Self Driving Car Nano Degree Program