Prediction of gaze direction using Convolutional Neural Networks for Autism diagnosis

Autism is a developmental disorder that affects social interaction and communication of children. The gold standard diagnostic tools are very difficult to use and time consuming. However, diagnostic could be deduced from child gaze preferences by looking a video with social and abstract scenes. In this work, we propose an algorithm based on convolutional neural networks to predict gaze direction for a fast and effective autism diagnosis. Early results show that our algorithm achieves real-time response and robust high accuracy for prediction of gaze direction.

READ FULL TEXT
research
11/23/2021

HybridGazeNet: Geometric model guided Convolutional Neural Networks for gaze estimation

As a critical cue for understanding human intention, human gaze provides...
research
07/04/2019

Believe It or Not, We Know What You Are Looking at!

By borrowing the wisdom of human in gaze following, we propose a two-sta...
research
07/03/2017

Efficient Eye Typing with 9-direction Gaze Estimation

Vision based text entry systems aim to help disabled people achieve text...
research
02/16/2023

Social Visual Behavior Analytics for Autism Therapy of Children Based on Automated Mutual Gaze Detection

Social visual behavior, as a type of non-verbal communication, plays a c...
research
09/04/2019

Understanding Human Gaze Communication by Spatio-Temporal Graph Reasoning

This paper addresses a new problem of understanding human gaze communica...
research
11/05/2022

HREyes: Design, Development, and Evaluation of a Novel Method for AUVs to Communicate Information and Gaze Direction

We present the design, development, and evaluation of HREyes: biomimetic...

Please sign up or login with your details

Forgot password? Click here to reset