Computer Vision model to detect face in the first frame of a video and to continue tracking it in the rest of the video. This is implemented in OpenCV 3.3.0 and Python 2.7
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Updated
Dec 31, 2017 - Python
Computer Vision model to detect face in the first frame of a video and to continue tracking it in the rest of the video. This is implemented in OpenCV 3.3.0 and Python 2.7
Kalman filter realised in python3
A python-based application that utilizes Kalman Filter to process data from GPS, speedometer, and accelerometer sensors to estimate the position of a vehicle.
Python implementation of popular filters
Tracks position of a vehicle by fusing data obtained from an MPU9250 and an optical displacement sensor using Kalman Filter.
This repository is created based on the projects opened at the Coursera Self-driving Cars specialization course, published by Toronto University. https://www.coursera.org/specializations/self-driving-cars
A Python package for (multiple) object tracking using recursive Bayesian filtering
Localization with Kalman filter
Utilizing YOLOv4 for Object Tracking and Incorporating Kalman Filter for UAV Trajectory Prediction.
Implementation of Kalman filter algorithm. This project serves as the foundation for using Kalman filter in IMU sensors and also future Extended Kalman Filter projects.
Simple Kalman Filter.
Robotic Vision lab and assignment from ECEN631
May 12th Kalman filter-based tracker demonstration
Differentiable Sequence Models
Implementation of the linear Kalman filter for 2d tracking
Collision Avoidance System (Robotics) - Implemented using ROS Noetic (with Python), YOLOv8, OpenCV, and Kalman Filter.
Implement the Kalman filter and establish a pipeline for pedestrian detection and tracking using YOLOv5 and the Hungarian algorithm
Explore the world of UAV-State-Estimation, a detailed Python repository focusing on 3D state estimation for unmanned aerial vehicles (UAVs) through the use of Kalman Filter methods. This repository uniquely merges theoretical frameworks and hands-on simulations, making it an ideal resource for both drone enthusiasts and experts in drone technology.
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