Attention Indexing Computer Vision POC for ripplecreate
-
Updated
Apr 1, 2022 - Python
Attention Indexing Computer Vision POC for ripplecreate
Experimental notebooks on blink detection problem by analizing it with simple thresholds, timeseries approach and a ml model.
A lightweight application crafted to gently remind you to blink your eyes during prolonged screen exposure.
This is the official code and data for paper "SynBlink and BlinkFormer: A Synthetic Dataset and Transformer-Based Method for Video Blink Detection", accepted by BMVC 2023.
Build on Python using Computer Vision libraries of Python (Dlib and OpenCV). It detects and counts the number of eye blinks in a video. It works on the concept of Eye aspect ratio.
A demo for iris and sclera segmentation using neural networks. This technique allows blink detection and classification.
Detección de parpadeo mediante deep learning
A multimodal face liveness detection module that can be used in the context of face anti-spoofing
Movement of mouse using Eye tracking feature and Blink Eye on Click of mouse.
Computer vision application to type based on detection of eyes blinking morse code.
Eye movement track + blink detection.
dlib blink detection a la weeping angels
Um teclado virtual projetado para proporcionar uma forma alternativa de interação, permitindo que os usuários controlem a digitação por meio de piscadas.
Eye blink detection with OpenCV and dlib implemented in Python
AI-Proctoring Framework runs in the background on the examinee’s machine, and tracks any kind of unwanted (Suspicious) activity of the candidate. Mouth Tracking, Blink Detection, Gaze Detection, Object Detection & Liveness Detection are few of the algorithms implemented in this Framework.
This repo contains, training material, dlib implementation, tensorflow implementation and an own made complete system implementation with a parse-controller.
face liveness detection activate, the script asks the person to generate an action, for example one of the actions they may ask you to do is smile, turn your face to the right, get angry, blink, etc. The actions are requested randomly, after fulfilling all the actions it generates a message saying "liveness successful" or "liveness fail"
Add a description, image, and links to the blink-detection topic page so that developers can more easily learn about it.
To associate your repository with the blink-detection topic, visit your repo's landing page and select "manage topics."