Feature Detection based on Haar Cascades in JavaScript (Viola-Jones-Lienhart et al Algorithm)

Viola-Jones face detection from scratch in WebAssembly

The face of a human is crucial for conveying identity. Computer scientists, Neuro scientists, and psychologists, all exploits this human feature using image processing techniques for commercial, and law enforcement applications. Likewise, this feature can be invited into classrooms to maintain records of students’ attendance. Con- temporary traditional way of recording attendance involves human intervention and requires cooperation of the students which is hectic and contribute towards waste of class time. An automated real-time classroom attendance system detects students from still image or video frame coming from a digital camera, and marks his/her attendance by recognizing them. The system utilizes Viola–Jones object detection framework which is capable of processing images extremely rapidly with high detec- tion rates. In the next stage, the detected face in the image is recognized using Local Binary Patterns Histogram.

Training a face detection cascade using Adaptive Boosting after Viola and Jones.

This project is part of the CS course 'Systems Engineering Meets Life Sciences I' at Goethe University Frankfurt. In this Computer Vision project, we present our first attempt at tackling the problem of traffic sign recognition using a systems engineering approach.

A face detection program in python using Viola-Jones algorithm.

A Voila-Jones face detector hardware implementation

A face detection algorithm using Viola-Jones' rapid object detection framework written in Julia

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

Gesture detect by viola-jones and cnn(based on opencv and caffe), able to detect and classify 5 kinds of pose, best 3ms/perframe on ARM-Firefly-RK3399

face detection using classical Viola-Jones method

Feature Detection based on Haar Cascades in PHP (Viola-Jones-Lienhart et al Algorithm)

Viola-Jones face detector.

Detection algorithms and applications from famous papers; simple theory; solid code.

Final Year Dissertation Project by Asis Rai

Various projects using Open CV

python implementation of the Viola-Jones algorithm in rapid face detection

The purpose of this project is to demonstrate the advantages of combining multiple CNNs to a common cascade structure. In contrast to training a single CNN only, the resulting classifier can be faster and more accurate at once. It can be used e.g. for the purpose of face detection.

Where all the state-of-the-art computer vision Algorithms meet

Viola Jones Object Detection Framework in C

The projects are part of the graduate-level course CSE-573 : Computer Vision and Image Processing [Spring 2019 @ UB_SUNY] Course Instructor : David Doerman (https://cse.buffalo.edu/~doermann/)

:eyes: Eyeball detection and eye gaze tracking using MATLAB by face detection, eye region detection, pupil detection and eye tracking.

Face Detection by AdaBoost learning. Conformal Geometric Algebra is applied for feature extraction.

This uses face detection with webcam.

Face Recognition algorithm implemented using Eigen Faces and Viola Jones Algorithm.

Python, C, RTL implementation of Viola Jones cascade classifier, using pretrained model from opencv.

👨👩 Viola Jones Face Detection

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Face Detection Application written in C++ using OpenCV

Course project for CSE 344 : Computer Vision.