There are 2 repositories under hog topic.
Artificial Intelligence Learning Notes.
HoG, PCA, PSO, Hard Negative Mining, Sliding Window, Edge Boxes, NMS
Training SVM classifier to recognize people expressions (emotions) on Fer2013 dataset
Vehicle detection, tracking and counting by SVM is trained with HOG features using OpenCV on c++.
[DEPRECATED] Traffic sign detector and classifier that uses dlib and its implementation of the Felzenszwalb's version of the Histogram of Oriented Gradients (HoG) detector
zAnalysis是基于Pascal语言编写的大型统计学开源库
Detect eye blinks based on eye aspect ratio (EAR) introduced by Soukupová and Čech in their 2016 paper, Real-Time Eye Blink Detection Using Facial Landmarks.
Histogram Of Oriented Gradients
HOG-based linear SVM for detecting vehicles (or any other object) in videos
Term 1, Project 5 - Udacity Self Driving Car Nanodegree
Object detection using feature-based algorithms in Rust. Compiles to WebAssembly.
Vehicle detection based on YOLO and SVM
使用HOG和SVM进行目标检测
This project uses Histogram of Oriented Gradients for pedestrian detection and Kalman Filter for tracking and prediction
A real-time human counter that uses HOG and SVM. Developed as project for the Computer Vision course at Sapienza University of Rome (2021-22)
Image Search Engine
This is "ready from box" face recognition app, based on Mediapipe, dlib and face_recognition modules.
Udacity Self Driving Car Nanodegree - Vehicle Detection
This algorithm counts occurrences of gradient orientation in localized portions of an image and visualize it in an image.
Computer Vision - Object Detection
Histogram of oriented gradients (HOG) on GPU
Classifier for CIFAR-10. Grayscaling, HOG, PCA, and RBF SVM. 62% test accuracy. Walkthrough on YouTube: https://youtu.be/gmTweV0eHhk
Face Recognition library
In this project 4 distinct tasks (gender detection (A1), smile detection (A2), face-shape recognition (B1), eye-color recognition (B2)) are adressed following 4 different approaches and exploiting the potentialities of CNNs and HOG descriptors along with SVMs.
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.