Deep learning based Gaze Detection model to control the mouse pointer of your computer.
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Updated
Nov 22, 2022 - Python
Deep learning based Gaze Detection model to control the mouse pointer of your computer.
This repository is related to estimating the driver's attention to the outside scene view as a point of gaze (PoG) w.r.t the gaze angles extracted from the driver facing view. We also explore analysis of gaze saliecny in form of heatmaps and yarbus plots.
Feeding an SVM w/ 2D human coordinates to estimate its visual focus of attention
Domain adaptation on gaze estimation from MPIIFaceGaze to ColumbiaGaze
Attention and Anxiety Analysis based on CNN
Estimate person gaze based on head orientation and feature landmarks
Computer-Pointer-Controller-OpenVINO is an application which uses a gaze detection model to control the mouse pointer movement. The input requires a video or a live stream from your webcam.
We present SCENE-pathy, a dataset and a set of baselines to study the visual selective attention (VSA) of people towards the 3D scene in which they are located
使用OpenCV部署眼睛凝视估计,包含C++和Python两个版本的程序,只依赖opencv库就可以运行,彻底摆脱对任何深度学习框架的依赖。
The project involves developing a method for robust, real-time pupil detection using computer vision techniques in OpenCV and Python, focusing on increasing accuracy and detection speed by reducing false edges from eyelids, eyelashes, and hair, and is suitable for integration into embedded architectures.
A data analysis and visualization repository for the visual experience database
A simple machine learning model used to estimate the direction of an person's gaze within an image.
Official Implementation of "Towards Self-Supervised Gaze Estimation"
A multimodal face liveness detection module that can be used in the context of face anti-spoofing
An Undergraduate Capstone Project under the Digital Signal Processing Laboratory of the University of the Philippines Diliman
ONNX implementation of "NITEC: Versatile Hand-Annotated Eye Contact Dataset for Ego-Vision Interaction" https://github.com/thohemp/nitec
Practical project for the course Machine Perception 2020 at ETH Zurich, where my team got the 1st place on the leaderboard.
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