ArticleSensors (Basel, Switzerland)2020
Hybrid Eye-Tracking on a Smartphone with CNN Feature Extraction and an Infrared 3D Model.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 53 citations in OpenAlex.
- Article
- The Feasibility of RGB-D Gaze Intention Measurement in Children with Autism Using Azure Kinect.Bioengineering (Basel, Switzerland) · 2025Article
- Development of a Magnetoresistive-Based Wearable Eye-Tracking System for Oculomotor Assessment in Neurological and Otoneurological Research-Preliminary In Vivo Tests.Brain sciences · 2023Article
- Vision-Based Eye Image Classification for Ophthalmic Measurement Systems.Sensors (Basel, Switzerland) · 2022Article
- Application of Transformer Models to Landslide Susceptibility Mapping.Sensors (Basel, Switzerland) · 2022Article
- Eye and Head Movement Recordings Using Smartphones for Telemedicine Applications: Measurements of Accuracy and Precision.Frontiers in neurology · 2022Article
- A novel method for peanut variety identification and classification by Improved VGG16.Scientific reports · 2021Article
- Recent updates of eye movement abnormalities in patients with schizophrenia: A scoping review.Psychiatry and clinical neurosciences · 2021Article
- Imaging Time Series of Eye Tracking Data to Classify Attentional States.Frontiers in neuroscience · 2021Article
- A Novel User Emotional Interaction Design Model Using Long and Short-Term Memory Networks and Deep Learning.Frontiers in psychology · 2021Article
- Advances in Multimodal Emotion Recognition Based on Brain-Computer Interfaces.Brain sciences · 2020Review
- Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges.Sensors (Basel, Switzerland) · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
This paper describes a low-cost, robust, and accurate remote eye-tracking system that uses an industrial prototype smartphone with integrated infrared illumination and camera. Numerous studies have demonstrated the beneficial use of eye-tracking in domains such as neurological and neuropsychiatric testing, advertising evaluation, pilot training, and automotive safety. Remote eye-tracking on a smartphone could enable the significant growth in the deployment of applications in these domains. Our system uses a 3D gaze-estimation model that enables accurate point-of-gaze (PoG) estimation with free head and device motion. To accurately determine the input eye features (pupil center and corneal reflections), the system uses Convolutional Neural Networks (CNNs) together with a novel center-of-mass output layer. The use of CNNs improves the system's robustness to the significant variability in the appearance of eye-images found in handheld eye trackers. The system was tested with 8 subjects with the device free to move in their hands and produced a gaze bias of 0.72°. Our hybrid approach that uses artificial illumination, a 3D gaze-estimation model, and a CNN feature extractor achieved an accuracy that is significantly (400%) better than current eye-tracking systems on smartphones that use natural illumination and machine-learning techniques to estimate the PoG.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.