EyeSpyVR

Ahuja, Karan; Islam, Rahul; Parashar, Varun; Dey, Kuntal; Harrison, Chris; Goel, Mayank

doi:10.1145/3214260

Cited by 36 publications

(7 citation statements)

References 25 publications

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“…The complexity of the images affects the accuracy of the scheme [150,170]. Tasks that are based on dynamic stimuli elaborate the goal-oriented visual search approach of individuals as they typically are asked to track dynamic stimuli, such as moving target [6,12,14,48,56,61,64,67,88,91,106,118,136,139,[148][149][150]165,172,173,175] or video recordings [23,85,133,134,143].…”

Section: Continuous Vs Controlled Visual Stimulimentioning

confidence: 99%

“…The majority of the works in implicit gaze-based authentication focus on evaluating the proposed schemes towards performance (i.e., efficiency of the classification mechanisms) and explore the efficiency of different features against identification accuracy [26]. Several metrics have been used towards this direction, such as equal error rate -EER (e.g., in [55,56,85,148,150,172]), receiver operating characteristic curve -ROC curve (e.g., in [6,13,25,132,149]), false acceptance rate -FAR (e.g., in [55,88,89,97,132,172]), and false rejection rate -FRR (e.g., in [55,66,88,89,132,150,172]).…”

Section: Performance Evaluationmentioning

confidence: 99%

“…While studying the long-term use is critical for authentication, very few works [6,92,118,150,173] report such studies. A degradation of accuracy is observed with time regardless of the type of visual stimuli used [92,150].…”

Section: Long Term Evaluationmentioning

confidence: 99%

“…desktop computers but being also available on head-mounted displays [6,45,49,52,103], handheld mobile devices [73], and public displays [171]. Today, laptops such as Alienware 17 R4 and Acer Predator 21 X come with integrated eye trackers, and smartphones such as the iPhone X and Huawei Mate 30 Pro are equipped with front-facing depth cameras, capable of accurate gaze estimation.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The Role of Eye Gaze in Security and Privacy Applications: Survey and Future HCI Research Directions

Katsini¹,

Abdrabou

Raptis³

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

116

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For the past 20 years, researchers have investigated the use of eye tracking in security applications. We present a holistic view on gaze-based security applications. In particular, we canvassed the literature and classify the utility of gaze in security applications into a) authentication, b) privacy protection, and c) gaze monitoring during security critical tasks. This allows us to chart several research directions, most importantly 1) conducting field studies of implicit and explicit gaze-based authentication due to recent advances in eye tracking, 2) research on gaze-based privacy protection and gaze monitoring in security critical tasks which are under-investigated yet very promising areas, and 3) understanding the privacy implications of pervasive eye tracking. We discuss the most promising opportunities and most pressing challenges of eye tracking for security that will shape research in gaze-based security applications for the next decade.

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Section: Continuous Vs Controlled Visual Stimulimentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Long Term Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Role of Eye Gaze in Security and Privacy Applications: Survey and Future HCI Research Directions

Katsini¹,

Abdrabou

Raptis³

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

116

View full text Add to dashboard Cite

show abstract

“…Beside IMU sensors, an up to date smartphone device contains efficient GPU and high resolution screen. Thanks to those features, smartphones can be used to construct a relatively affordable component of virtual reality glasses/helmets [5]. Head gestures require a pattern recognition algorithm that would enable unambiguous recognition of user head trajectory.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Pattern Recognition Methods for Head Gesture-Based Interface of a Virtual Reality Helmet Equipped with a Single IMU Sensor

Hachaj

Piekarczyk

2019

Sensors

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The motivation of this paper is to examine the effectiveness of state-of-the-art and newly proposed motion capture pattern recognition methods in the task of head gesture classifications. The head gestures are designed for a user interface that utilizes a virtual reality helmet equipped with an internal measurement unit (IMU) sensor that has 6-axis accelerometer and gyroscope. We will validate a classifier that uses Principal Components Analysis (PCA)-based features with various numbers of dimensions, a two-stage PCA-based method, a feedforward artificial neural network, and random forest. Moreover, we will also propose a Dynamic Time Warping (DTW) classifier trained with extension of DTW Barycenter Averaging (DBA) algorithm that utilizes quaternion averaging and a bagged variation of previous method (DTWb) that utilizes many DTW classifiers that perform voting. The evaluation has been performed on 975 head gesture recordings in seven classes acquired from 12 persons. The highest value of recognition rate in a leave-one-out test has been obtained for DTWb and it equals 0.975 (0.026 better than the best of state-of-the-art methods to which we have compared our approach). Among the most important applications of the proposed method is improving life quality for people who are disabled below the neck by supporting, for example, an assistive autonomous power chair with a head gesture interface or remote controlled interfaces in robotics.

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A Literature Review on Virtual Reality Authentication

Jones

Duezguen

Mayer

et al. 2021

Human Aspects of Information Security and Assurance

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As virtual reality (VR) sees an increase in use in several domains such as retail, education, military; a secure authentication scheme for VR devices is necessary to keep users' personal information safe. A smaller section of research focuses on the authentication schemes of VR devices. To further the understanding of this topic, we conducted a detailed literature review of VR authentication by exploring papers published till October 2020. A total of N = 29 papers were found. While many papers evaluate the accuracy of authentication methods, few conduct detailed user studies. In the user studies done, we found a lack of focus on diverse populations such as the elderly, with the mean age of the participants being 25.11. Our findings from the literature review give a detailed overview of VR-based authentication schemes and highlight trends as well as current research gaps. These findings drive future research direction to create robust and usable authentication strategies.

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EyeSpyVR

Cited by 36 publications

References 25 publications

The Role of Eye Gaze in Security and Privacy Applications: Survey and Future HCI Research Directions

The Role of Eye Gaze in Security and Privacy Applications: Survey and Future HCI Research Directions

Evaluation of Pattern Recognition Methods for Head Gesture-Based Interface of a Virtual Reality Helmet Equipped with a Single IMU Sensor

A Literature Review on Virtual Reality Authentication

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