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Found 35 papers, 3 papers with code
A Trainable Feature Extractor Module for Deep Neural Networks and Scanpath Classification
In this paper we propose a trainable feature extraction module for deep neural networks.
Normalized Validity Scores for DNNs in Regression based Eye Feature Extraction
We propose a normalization in the loss formulation, which improves the accuracy of the entire approach due to the numerical balance of the normalized inaccuracy.
An Initialization Schema for Neuronal Networks on Tabular Data
The proposed approach shows a simple but effective approach for initializing the first hidden layer in neural networks.
Resource saving taxonomy classification with k-mer distributions and machine learning
In addition, we propose a feature space data set balancing approach, which allows reducing the data set for training and improves the performance of the classifiers.
Area of interest adaption using feature importance
In qualitative analysis, the algorithms presented allow the AOIs to be adapted to the data, which means that errors and inaccuracies in eye tracking data can be better compensated for.
A temporally quantized distribution of pupil diameters as a new feature for cognitive load classification
The feature consists of a temporal segmentation of the eye tracking recordings.
One step closer to EEG based eye tracking
In this paper, we present two approaches and algorithms that adapt areas of interest We present a new deep neural network (DNN) that can be used to directly determine gaze position using EEG data.
Deep Learning-Based Position Detection for Hydraulic Cylinders Using Scattering Parameters
A typical traditional method is to excite electromagnetic waves in the cylinder structure and analytically solve the piston position based on the scattering parameters measured by a sensor.
Technical Report: Combining knowledge from Transfer Learning during training and Wide Resnets
This idea comes from transfer learning, which uses networks pre-trained on other data and extracts different levels of the network as input for the new task.
Where and What: Driver Attention-based Object Detection
Human drivers use their attentional mechanisms to focus on critical objects and make decisions while driving.
Gaze-based Object Detection in the Wild
For this purpose, we explore different sizes of temporal windows, which serve as a basis for the computation of heatmaps, i. e., the spatial distribution of the gaze data.
Pistol: Pupil Invisible Supportive Tool to extract Pupil, Iris, Eye Opening, Eye Movements, Pupil and Iris Gaze Vector, and 2D as well as 3D Gaze
This paper describes a feature extraction and gaze estimation software, named \textit{Pistol} that can be used with Pupil Invisible projects and other eye trackers in the future.
Tensor Normalization and Full Distribution Training
In this work, we introduce pixel wise tensor normalization, which is inserted after rectifier linear units and, together with batch normalization, provides a significant improvement in the accuracy of modern deep neural networks.
Maximum and Leaky Maximum Propagation
In this work, we present an alternative to conventional residual connections, which is inspired by maxout nets.
TEyeD: Over 20 million real-world eye images with Pupil, Eyelid, and Iris 2D and 3D Segmentations, 2D and 3D Landmarks, 3D Eyeball, Gaze Vector, and Eye Movement Types
The data set includes 2D and 3D landmarks, semantic segmentation, 3D eyeball annotation and the gaze vector and eye movement types for all images.
1000 Pupil Segmentations in a Second using Haar Like Features and Statistical Learning
In this paper we present a new approach for pupil segmentation.
A Multimodal Eye Movement Dataset and a Multimodal Eye Movement Segmentation Analysis
We present a new dataset with annotated eye movements.
The Gaze and Mouse Signal as additional Source for User Fingerprints in Browser Applications
However, human gaze acquisition in the browser also has disadvantages, such as inaccuracies via webcam and the restriction that the user must first allow access to the camera.
Explainable Online Validation of Machine Learning Models for Practical Applications
The presented algorithm based on conditional probabilities is also online capable and requires only a fraction of memory compared to the kNN algorithm.
Weight and Gradient Centralization in Deep Neural Networks
Batch normalization is currently the most widely used variant of internal normalization for deep neural networks.
Rotated Ring, Radial and Depth Wise Separable Radial Convolutions
We also discuss the influence of purely rotational invariant features on accuracy.
Multi Layer Neural Networks as Replacement for Pooling Operations
This kind of pooling allows for the integration of multi-layer neural networks directly into a model as a pooling operation by restructuring the data and, as a result, learnin complex pooling operations.
Differential Privacy for Eye Tracking with Temporal Correlations
New generation head-mounted displays, such as VR and AR glasses, are coming into the market with already integrated eye tracking and are expected to enable novel ways of human-computer interaction in numerous applications.
Reinforcement learning for the privacy preservation and manipulation of eye tracking data
In this paper, we present an approach based on reinforcement learning for eye tracking data manipulation.
Fully Convolutional Neural Networks for Raw Eye Tracking Data Segmentation, Generation, and Reconstruction
In this paper, we use fully convolutional neural networks for the semantic segmentation of eye tracking data.
Training Decision Trees as Replacement for Convolution Layers
Our approach reduces the complexity of convolutions by replacing it with binary decisions.
Learning to Validate the Quality of Detected Landmarks
In addition, we evaluated the impact of the validation loss on the landmark accuracy based on uniform sampling.
Eye movement simulation and detector creation to reduce laborious parameter adjustments
Eye movements hold information about human perception, intention and cognitive state.
PuRe: Robust pupil detection for real-time pervasive eye tracking
state-of-the-art algorithms by 25. 05 and 10. 94 percentage points, respectively, demonstrating the meaningfulness of PuRe's confidence measure.
Fast camera focus estimation for gaze-based focus control
Many cameras implement auto-focus functionality.
PupilNet v2.0: Convolutional Neural Networks for CPU based real time Robust Pupil Detection
Real-time, accurate, and robust pupil detection is an essential prerequisite for pervasive video-based eye-tracking.
PupilNet: Convolutional Neural Networks for Robust Pupil Detection
Real-time, accurate, and robust pupil detection is an essential prerequisite for pervasive video-based eye-tracking.
Bayesian Identification of Fixations, Saccades, and Smooth Pursuits
Smooth pursuit eye movements provide meaningful insights and information on subject's behavior and health and may, in particular situations, disturb the performance of typical fixation/saccade classification algorithms.
ElSe: Ellipse Selection for Robust Pupil Detection in Real-World Environments
Fast and robust pupil detection is an essential prerequisite for video-based eye-tracking in real-world settings.
