Udacity CarND - Vehicle Detection and Tracking
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Updated
Mar 7, 2017 - Python
Udacity CarND - Vehicle Detection and Tracking
My DATAML300 - Computer vision solutions.
Morse code to text converter by detecting eye blink on the basis of EAR threshold using RANDOMFORESTCLASSIFIER model and HOG+SVM model
A project for real time detection and counting of number of human in a photo and video using HOG and SVM.
Udacity Self Driving Car Engineer Project - Vehicle Detection using HOG
Numpy Implementation of classic computer vision feature extraction algorithm.
Human ear classification after feature extraction.
Simple detector based on histogram of oriented gradients and support vector machines
Face Detection Using HOG
Car detection algorithm with classical computer vision (no deep learning) using OpenCV and Scipy
UIBK project: Comparing the performance of SIFT, SURF and HOG for image classification.
car detection and tracking
Computer Vision Driverless car object detection assignment
Identification of individual salmons using CNN and HoG approach
A live drowsiness detection system made to run on a single board computer like raspi. It has been tested with different extreme parameters of distance and spectacles. Can be a huge product to run on cars and prevent accidents as the system runs with 0% internet connectivity.
This project implements algorithms for detecting and recognizing characters from the Flintstone family using the HOG method along with a sliding window approach.
Detects facial landmarks in real-time from the input feed of a webcam/usb-camera/pi-cam using a HOG + Linear SVM model.
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