Inference-Time Gaze Refinement for Micro-Expression Recognition: Enhancing Event-Based Eye Tracking with Motion-Aware Post-Processing
School of Computing（计算学院）；Information Systems, Singapore Management University, Singapore（信息系统，新加坡管理大学，新加坡）
Nuwan Bandara, Thivya Kandappu, Archan Misra
备注：
Accepted at 4DMR@IJCAI25: International IJCAI Workshop on 1st Challenge and Workshop for 4D Micro-Expression Recognition for Mind Reading, August 29, 2025, Guangzhou, China
Event-based eye tracking holds significant promise for fine-grained cognitive state inference, offering high temporal resolution and robustness to motion artifacts, critical features for decoding subtle mental states such as attention, confusion, or fatigue. In this work, we introduce a model-agnostic, inference-time refinement framework designed to enhance the output of existing event-based gaze estimation models without modifying their architecture or requiring retraining. Our method comprises two key post-processing modules: (i) Motion-Aware Median Filtering, which suppresses blink-induced spikes while preserving natural gaze dynamics, and (ii) Optical Flow-Based Local Refinement, which aligns gaze predictions with cumulative event motion to reduce spatial jitter and temporal discontinuities. To complement traditional spatial accuracy metrics, we propose a novel Jitter Metric that captures the temporal smoothness of predicted gaze trajectories based on velocity regularity and local signal complexity. Together, these contributions significantly improve the consistency of event-based gaze signals, making them better suited for downstream tasks such as micro-expression analysis and mind-state decoding. Our results demonstrate consistent improvements across multiple baseline models on controlled datasets, laying the groundwork for future integration with multimodal affect recognition systems in real-world environments. Our code implementations can be found at https://github.com/eye-tracking-for-physiological-sensing/EyeLoRiN.
Eye gaze estimation and simultaneous semantic understanding of a user through eye images is a crucial component in Virtual and Mixed Reality; enabling energy efficient rendering, multi-focal displays and effective interaction with 3D content. In head-mounted VR/MR devices the eyes are imaged off-axis to avoid blocking the user's gaze, this view-point makes drawing eye related inferences very challenging. In this work, we present EyeNet, the first single deep neural network which solves multiple heterogeneous tasks related to eye gaze estimation and semantic user understanding for an off-axis c…
With the emergence of Virtual and Mixed Reality (XR) devices, eye tracking has received significant attention in the computer vision community. Eye gaze estimation is a crucial component in XR -- enabling energy efficient rendering, multi-focal displays, and effective interaction with content. In head-mounted XR devices, the eyes are imaged off-axis to avoid blocking the field of view. This leads to increased challenges in inferring eye related quantities and simultaneously provides an opportunity to develop accurate and robust learning based approaches. To this end, we present MagicEyes, the …
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. In offline mode, our software extracts multiple features from the eye including, the pupil and iris ellipse, eye aperture, pupil vector, iris vector, eye movement types from pupil and iris velocities, marker detection, marker distance, 2D gaze estimation for the pupil center, iris center, pupil vector, and iris vector using Levenberg Marquart fitting and neural networks. The gaze signal is computed in 2D for each eye …
Indian Institute of Science（印度科学学院）；Indian Institute of Technology, Madras（马德拉斯印度理工学院）；Indian Institute of Information Technology, Kalyani（卡利亚尼印度信息技术学院）
Background: People with severe speech and motor impairment (SSMI) often uses a technique called eye pointing to communicate with outside world. One of their parents, caretakers or teachers hold a printed board in front of them and by analyzing their eye gaze manually, their intentions are interpreted. This technique is often error prone and time consuming and depends on a single caretaker. Objective: We aimed to automate the eye tracking process electronically by using commercially available tablet, computer or laptop and without requiring any dedicated hardware for eye gaze tracking. The eye …
Massachusetts Institute of Technology (MIT)（麻省理工学院）；Chalmers University of Technology（查尔姆斯理工大学）；SAFER
Accurate, robust, inexpensive gaze tracking in the car can help keep a driver safe by facilitating the more effective study of how to improve (1) vehicle interfaces and (2) the design of future Advanced Driver Assistance Systems. In this paper, we estimate head pose and eye pose from monocular video using methods developed extensively in prior work and ask two new interesting questions. First, how much better can we classify driver gaze using head and eye pose versus just using head pose? Second, are there individual-specific gaze strategies that strongly correlate with how much gaze classific…
Analyzing the gaze accuracy characteristics of an eye tracker is a critical task as its gaze data is frequently affected by non-ideal operating conditions in various consumer eye tracking applications. In this study, gaze error patterns produced by a commercial eye tracking device were studied with the help of machine learning algorithms, such as classifiers and regression models. Gaze data were collected from a group of participants under multiple conditions that commonly affect eye trackers operating on desktop and handheld platforms. These conditions (referred here as error sources) include…
This paper presents the selective use of eye-gaze information in learning human actions in Atari games. Vast evidence suggests that our eye movement convey a wealth of information about the direction of our attention and mental states and encode the information necessary to complete a task. Based on this evidence, we hypothesize that selective use of eye-gaze, as a clue for attention direction, will enhance the learning from demonstration. For this purpose, we propose a selective eye-gaze augmentation (SEA) network that learns when to use the eye-gaze information. The proposed network architec…
University of Cambridge（剑桥大学）；Microsoft（微软）；Carnegie Mellon University（卡内基梅隆大学）；Max Planck Institute for Informatics（马克斯·普朗克信息学研究所）
We present GazeDirector, a new approach for eye gaze redirection that uses model-fitting. Our method first tracks the eyes by fitting a multi-part eye region model to video frames using analysis-by-synthesis, thereby recovering eye region shape, texture, pose, and gaze simultaneously. It then redirects gaze by 1) warping the eyelids from the original image using a model-derived flow field, and 2) rendering and compositing synthesized 3D eyeballs onto the output image in a photorealistic manner. GazeDirector allows us to change where people are looking without person-specific training data, and…
Technological Institute of the Philippines（菲律宾理工学院）
Eye-GUIDE is an assistive communication tool designed for the paralyzed or physically impaired people who were unable to move parts of their bodies especially people whose communications are limited only to eye movements. The prototype consists of a camera and a computer. Camera captures images then it will be send to the computer, where the computer will be the one to interpret the data. Thus, Eye-GUIDE focuses on camera-based gaze tracking. The proponent designed the prototype to perform simple tasks and provides graphical user interface in order the paralyzed or physically impaired person c…
Max Planck Institute for Informatics（马克斯·普朗克信息学研究所）
3D gaze information is important for scene-centric attention analysis but accurate estimation and analysis of 3D gaze in real-world environments remains challenging. We present a novel 3D gaze estimation method for monocular head-mounted eye trackers. In contrast to previous work, our method does not aim to infer 3D eyeball poses but directly maps 2D pupil positions to 3D gaze directions in scene camera coordinate space. We first provide a detailed discussion of the 3D gaze estimation task and summarize different methods, including our own. We then evaluate the performance of different 3D gaze…
University of Stuttgart（斯图加特大学）；University of Southampton（南安普顿大学）
World-wide-web, with the website and webpage as the main interface, facilitates the dissemination of important information. Hence it is crucial to optimize them for better user interaction, which is primarily done by analyzing users' behavior, especially users' eye-gaze locations. However, gathering these data is still considered to be labor and time intensive. In this work, we enable the development of automatic eye-gaze estimations given a website screenshots as the input. This is done by the curation of a unified dataset that consists of website screenshots, eye-gaze heatmap and website's l…
University of Science and Technology of China（中国科学技术大学）；Carnegie Mellon University（卡内基梅隆大学）
In recent years, head-mounted near-eye display devices have become the key hardware foundation for virtual reality and augmented reality. Thus head-mounted gaze tracking technology has received attention as an essential part of human-computer interaction. However, unavoidable slippage of head-mounted devices (HMD) often results higher gaze tracking errors and hinders the practical usage of HMD. To tackle this problem, we propose a slippage-robust gaze tracking for near-eye display method based on the aspheric eyeball model and accurately compute the eyeball optical axis and rotation center. We…
HuaZhong University of Science and Technology（华中科技大学）
Eye gaze estimation has become increasingly significant in computer vision.In this paper,we systematically study the mainstream of eye gaze estimation methods,propose a novel methodology to estimate eye gaze points and eye gaze directions simultaneously.First,we construct a local sharing network for feature extraction of gaze points and gaze directions estimation,which can reduce network computational parameters and converge quickly;Second,we propose a Multiview Multitask Learning (MTL) framework,for gaze directions,a coplanar constraint is proposed for the left and right eyes,for gaze points,…
Gaze estimation is the fundamental basis for many visual tasks. Yet, the high cost of acquiring gaze datasets with 3D annotations hinders the optimization and application of gaze estimation models. In this work, we propose a novel Head-Eye redirection parametric model based on Neural Radiance Field, which allows dense gaze data generation with view consistency and accurate gaze direction. Moreover, our head-eye redirection parametric model can decouple the face and eyes for separate neural rendering, so it can achieve the purpose of separately controlling the attributes of the face, identity, …
Despite a revolution in the pervasiveness of video cameras in our daily lives, one of the most meaningful forms of nonverbal affective communication, interpersonal eye gaze, i.e. eye gaze relative to a conversation partner, is not available from common video. We introduce the Interpersonal-Calibrating Eye-gaze Encoder (ICE), which automatically extracts interpersonal gaze from video recordings without specialized hardware and without prior knowledge of participant locations. Leveraging the intuition that individuals spend a large portion of a conversation looking at each other enables the ICE …
Pupil Labs UG（Pupil Labs公司）；Max Planck Institute for Informatics（马克斯·普朗克信息学研究所）
Commercial head-mounted eye trackers provide useful features to customers in industry and research but are expensive and rely on closed source hardware and software. This limits the application areas and use of mobile eye tracking to expert users and inhibits user-driven development, customisation, and extension. In this paper we present Pupil -- an accessible, affordable, and extensible open source platform for mobile eye tracking and gaze-based interaction. Pupil comprises 1) a light-weight headset with high-resolution cameras, 2) an open source software framework for mobile eye tracking, as…
We present a novel multistream network that learns robust eye representations for gaze estimation. We first create a synthetic dataset containing eye region masks detailing the visible eyeball and iris using a simulator. We then perform eye region segmentation with a U-Net type model which we later use to generate eye region masks for real-world eye images. Next, we pretrain an eye image encoder in the real domain with self-supervised contrastive learning to learn generalized eye representations. Finally, this pretrained eye encoder, along with two additional encoders for visible eyeball regio…
Automatic eye gaze estimation has interested researchers for a while now. In this paper, we propose an unsupervised learning based method for estimating the eye gaze region. To train the proposed network "Ize-Net" in self-supervised manner, we collect a large `in the wild' dataset containing 1,54,251 images from the web. For the images in the database, we divide the gaze into three regions based on an automatic technique based on pupil-centers localization and then use a feature-based technique to determine the gaze region. The performance is evaluated on the Tablet Gaze and CAVE datasets by f…
Estimation eye gaze direction is useful in various human-computer interaction tasks. Knowledge of gaze direction can give valuable information regarding users point of attention. Certain patterns of eye movements known as eye accessing cues are reported to be related to the cognitive processes in the human brain. We propose a real-time framework for the classification of eye gaze direction and estimation of eye accessing cues. In the first stage, the algorithm detects faces using a modified version of the Viola-Jones algorithm. A rough eye region is obtained using geometric relations and facia…
Peking University（北京大学）；Southern University of Science and Technology（南方科技大学）
Hearing-impaired listeners usually have troubles attending target talker in multi-talker scenes, even with hearing aids (HAs). The problem can be solved with eye-gaze steering HAs, which requires listeners eye-gazing on the target. In a situation where head rotates, eye-gaze is subject to both behaviors of saccade and head rotation. However, existing methods of eye-gaze estimation did not work reliably, since the listener's strategy of eye-gaze varies and measurements of the two behaviors were not properly combined. Besides, existing methods were based on hand-craft features, which could overl…
Imperial College London（帝国理工学院）；Data Science Institute（数据科学研究所）
Eye movements have long been studied as a window into the attentional mechanisms of the human brain and made accessible as novelty style human-machine interfaces. However, not everything that we gaze upon, is something we want to interact with; this is known as the Midas Touch problem for gaze interfaces. To overcome the Midas Touch problem, present interfaces tend not to rely on natural gaze cues, but rather use dwell time or gaze gestures. Here we present an entirely data-driven approach to decode human intention for object manipulation tasks based solely on natural gaze cues. We run data co…
We explore techniques for eye gaze estimation using machine learning. Eye gaze estimation is a common problem for various behavior analysis and human-computer interfaces. The purpose of this work is to discuss various model types for eye gaze estimation and present the results from predicting gaze direction using eye landmarks in unconstrained settings. In unconstrained real-world settings, feature-based and model-based methods are outperformed by recent appearance-based methods due to factors like illumination changes and other visual artifacts. We discuss a learning-based method for eye regi…
Department of Computer Science University of the Philippines（菲律宾大学计算机科学系（菲律宾大学））
Eye movements are intricate and dynamic events that contain a wealth of information about the subject and the stimuli. We propose an abstract representation of eye movements that preserve the important nuances in gaze behavior while being stimuli-agnostic. We consider eye movements as raw position and velocity signals and train separate deep temporal convolutional autoencoders. The autoencoders learn micro-scale and macro-scale representations that correspond to the fast and slow features of eye movements. We evaluate the joint representations with a linear classifier fitted on various classif…
Accurate eye segmentation can improve eye-gaze estimation and support interactive computing based on visual attention; however, existing eye segmentation methods suffer from issues such as person-dependent accuracy, lack of robustness, and an inability to be run in real-time. Here, we present the RITnet model, which is a deep neural network that combines U-Net and DenseNet. RITnet is under 1 MB and achieves 95.3\% accuracy on the 2019 OpenEDS Semantic Segmentation challenge. Using a GeForce GTX 1080 Ti, RITnet tracks at $>$ 300Hz, enabling real-time gaze tracking applications. Pre-trained mode…
Islamic University of Technology（伊斯兰技术大学）；University of Manitoba（曼尼托巴大学）；National University, Bangladesh（孟加拉国国立大学）
Human intention is an internal, mental characterization for acquiring desired information. From interactive interfaces containing either textual or graphical information, intention to perceive desired information is subjective and strongly connected with eye gaze. In this work, we determine such intention by analyzing real-time eye gaze data with a low-cost regular webcam. We extracted unique features (e.g., Fixation Count, Eye Movement Ratio) from the eye gaze data of 31 participants to generate a dataset containing 124 samples of visual intention for perceiving textual or graphical informati…
University of Cambridge（剑桥大学）；Max Planck Institute for Informatics（马克斯·普朗克信息学研究所）
Images of the eye are key in several computer vision problems, such as shape registration and gaze estimation. Recent large-scale supervised methods for these problems require time-consuming data collection and manual annotation, which can be unreliable. We propose synthesizing perfectly labelled photo-realistic training data in a fraction of the time. We used computer graphics techniques to build a collection of dynamic eye-region models from head scan geometry. These were randomly posed to synthesize close-up eye images for a wide range of head poses, gaze directions, and illumination condit…
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
INESC-ID（INESC-ID（葡萄牙国家系统与计算机工程研究所））；Instituto Superior Técnico（里斯本高等技术学院）；Universidade de Lisboa（里斯本大学）；School of Information Systems（信息系统学院）；Queensland University of Technology（昆士兰科技大学）；Grupo Lusíadas（卢西亚达斯集团）
This paper proposes a novel multimodal DL architecture incorporating medical images and eye-tracking data for abnormality detection in chest x-rays. Our results show that applying eye gaze data directly into DL architectures does not show superior predictive performance in abnormality detection chest X-rays. These results support other works in the literature and suggest that human-generated data, such as eye gaze, needs a more thorough investigation before being applied to DL architectures.
Sri Jayachamarajendra College of Engineering（斯里贾亚查马拉詹德拉工程学院）；University of North Texas（北德克萨斯大学）
Study of eye-movement is being employed in Human Computer Interaction (HCI) research. Eye - gaze tracking is one of the most challenging problems in the area of computer vision. The goal of this paper is to present a review of latest research in this continued growth of remote eye-gaze tracking. This overview includes the basic definitions and terminologies, recent advances in the field and finally the need of future development in the field.
TalkingEyes: Pluralistic Speech-Driven 3D Eye Gaze Animation
School of Informatics, Xiamen University（厦门大学信息学院）；China Mobile (Hangzhou) Information Technology Co., Ltd.（中国移动（杭州）信息技术有限公司）；Department of Computer Science, City University of Hong Kong（香港城市大学计算机科学系）
Indian Institute of Technology（印度理工学院）；Indian Institute of Information Technology（印度信息技术学院）
A user's eyes provide means for Human Computer Interaction (HCI) research as an important modal. The time to time scientific explorations of the eye has already seen an upsurge of the benefits in HCI applications from gaze estimation to the measure of attentiveness of a user looking at a screen for a given time period. The eye tracking system as an assisting, interactive tool can be incorporated by physically disabled individuals, fitted best for those who have eyes as only a limited set of communication. The threefold objective of this paper is - 1. To introduce a neural network based archite…
Indian Institute of Technology Kharagpur（印度理工学院卡哈拉格普尔分校）
Eye movements play a vital role in perceiving the world. Eye gaze can give a direct indication of the users point of attention, which can be useful in improving human-computer interaction. Gaze estimation in a non-intrusive manner can make human-computer interaction more natural. Eye tracking can be used for several applications such as fatigue detection, biometric authentication, disease diagnosis, activity recognition, alertness level estimation, gaze-contingent display, human-computer interaction, etc. Even though eye-tracking technology has been around for many decades, it has not found mu…
National University of Ireland Galway（爱尔兰国立大学戈尔韦分校）；Xperi Corporation（Xperi公司）
Accurate and efficient eye gaze estimation is important for emerging consumer electronic systems such as driver monitoring systems and novel user interfaces. Such systems are required to operate reliably in difficult, unconstrained environments with low power consumption and at minimal cost. In this paper a new hardware friendly, convolutional neural network model with minimal computational requirements is introduced and assessed for efficient appearance-based gaze estimation. The model is tested and compared against existing appearance based CNN approaches, achieving better eye gaze accuracy …
University of California Berkeley（加州大学伯克利分校）；Stanford University（斯坦福大学）；KTH Royal Institute of Technology（瑞典皇家理工学院）
The cameras in modern gaze-tracking systems suffer from fundamental bandwidth and power limitations, constraining data acquisition speed to 300 Hz realistically. This obstructs the use of mobile eye trackers to perform, e.g., low latency predictive rendering, or to study quick and subtle eye motions like microsaccades using head-mounted devices in the wild. Here, we propose a hybrid frame-event-based near-eye gaze tracking system offering update rates beyond 10,000 Hz with an accuracy that matches that of high-end desktop-mounted commercial trackers when evaluated in the same conditions. Our s…
Shandong University（山东大学）；University of Trento（特伦托大学）；Texas State University（德克萨斯州立大学）
Gaze correction aims to redirect the person's gaze into the camera by manipulating the eye region, and it can be considered as a specific image resynthesis problem. Gaze correction has a wide range of applications in real life, such as taking a picture with staring at the camera. In this paper, we propose a novel method that is based on the inpainting model to learn from the face image to fill in the missing eye regions with new contents representing corrected eye gaze. Moreover, our model does not require the training dataset labeled with the specific head pose and eye angle information, thus…
Rather than regressing gaze direction directly from images, we show that adding a 3D shape model can: i) improve gaze estimation accuracy, ii) perform well with lower resolution inputs and iii) provide a richer understanding of the eye-region and its constituent gaze system. Specifically, we use an `eyes and nose' 3D morphable model (3DMM) to capture the eye-region 3D facial geometry and appearance and we equip this with a geometric vergence model of gaze to give an `active-gaze 3DMM'. We show that our approach achieves state-of-the-art results on the Eyediap dataset and we present an ablation…
Model-based eye tracking has been a dominant approach for eye gaze tracking because of its ability to generalize to different subjects, without the need of any training data and eye gaze annotations. Model-based eye tracking, however, is susceptible to eye feature detection errors, in particular for eye tracking in the wild. To address this issue, we propose a Bayesian framework for model-based eye tracking. The proposed system consists of a cascade-Bayesian Convolutional Neural Network (c-BCNN) to capture the probabilistic relationships between eye appearance and its landmarks, and a geometri…
Supporting Mitosis Detection AI Training with Inter-Observer Eye-Gaze Consistencies
University of California, Los Angeles（加利福尼亚大学洛杉矶分校）；University of Illinois, Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；UCLA David Geffen School of Medicine（加州大学洛杉矶分校大卫·格芬医学院）；Kansas University Medical Center（堪萨斯大学医学中心）
Universitat de Barcelona（巴塞罗那大学）；Computer Vision Center（计算机视觉中心）；Facebook Reality Labs（Facebook现实实验室）；Texas State University（德克萨斯州立大学）
State-of-the-art appearance-based gaze estimation methods, usually based on deep learning techniques, mainly rely on static features. However, temporal trace of eye gaze contains useful information for estimating a given gaze point. For example, approaches leveraging sequential eye gaze information when applied to remote or low-resolution image scenarios with off-the-shelf cameras are showing promising results. The magnitude of contribution from temporal gaze trace is yet unclear for higher resolution/frame rate imaging systems, in which more detailed information about an eye is captured. In t…
This paper presents a framework for recognition of human activity from egocentric video and eye tracking data obtained from a head-mounted eye tracker. Three channels of information such as eye movement, ego-motion, and visual features are combined for the classification of activities. Image features were extracted using a pre-trained convolutional neural network. Eye and ego-motion are quantized, and the windowed histograms are used as the features. The combination of features obtains better accuracy for activity classification as compared to individual features.
Gwangju Institute of Science and Technology（光州科学技术院）
Human-Computer Interaction(HCI) is a field that studies interactions between human users and computer systems. With the development of HCI, individuals or groups of people can use various digital technologies to achieve the optimal user experience. Human visual attention and visual intelligence are related to cognitive science, psychology, and marketing informatics, and are used in various applications of HCI. Gaze recognition is closely related to the HCI field because it is meaningful in that it can enhance understanding of basic human behavior. We can obtain reliable visual attention by the…
Eye-tracking technologies have been widely used in applications like psychological studies and human computer interactions (HCI). However, most current eye trackers focus on 2D point of gaze (PoG) estimation and cannot provide accurate gaze depth.Concerning future applications such as HCI with 3D displays, we propose a novel binocular eye tracking device with stereo stimuli to provide highly accurate 3D PoG estimation. In our device, the 3D stereo imaging system can provide users with a friendly and immersive 3D visual experience without wearing any accessories. The eye capturing system can di…
The Hong Kong University of Science and Technology（香港科技大学）
Vision-based autonomous driving through imitation learning mimics the behaviors of human drivers by training on pairs of data of raw driver-view images and actions. However, there are other cues, e.g. gaze behavior, available from human drivers that have yet to be exploited. Previous research has shown that novice human learners can benefit from observing experts' gaze patterns. We show here that deep neural networks can also benefit from this. We demonstrate different approaches to integrating gaze information into imitation networks. Our results show that the integration of gaze information …
China University of Mining and Technology（中国矿业大学）；Australian National University（澳大利亚国立大学）
Vision based text entry systems aim to help disabled people achieve text communication using eye movement. Most previous methods have employed an existing eye tracker to predict gaze direction and design an input method based upon that. However, these methods can result in eye tracking quality becoming easily affected by various factors and lengthy amounts of time for calibration. Our paper presents a novel efficient gaze based text input method, which has the advantage of low cost and robustness. Users can type in words by looking at an on-screen keyboard and blinking. Rather than estimate ga…
