Human Computer Interaction System Using Eye-Tracking Features

Agarkhed, Jayashree; Kulkarni, Ankita. S.; Hiroli, Nitin; Kulkarni, Jyoti B.; Jagde, Anjana; Pukale, Amrita

doi:10.1109/b-htc50970.2020.9297894

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…The eye-tracking interaction method has been evaluated to demonstrate its usability and performance as a substitute to the controller interaction method (Dong et al, 2020). It has a smaller activity requirement, and shows better robustness in interaction Frontiers in Energy Research frontiersin.org efficiency and response to target path changes (Agarkhed et al, 2020), which dramatically improves the interaction efficiency of conventional interaction methods. Eye tracking using HTC VIVE PRO EYE has an error within ±3 °and a maximum time error of about 58 ms when the user's head is not moving.…”

Section: Interactive Methodsmentioning

confidence: 99%

Data and model hybrid-driven virtual reality robot operating system

Liu

Lin²,

Lin³

et al. 2022

Front. Energy Res.

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To realize efficient remote human-computer interaction of robots, a robot remote operating system based on virtual reality and digital twin is proposed. The system builds a digital twin model based on the Unity 3D engine to establish a connection with the robot entity, assisting the online remote programming and real-time manipulation of the robot unit. The system uses HTC VIVE to build a virtual reality framework. To actualize the mutual drive between the real space and the virtual space, a mathematical model of the robot is constructed through the forward and inverse kinematics of the robot. Through the combination of eye-tracking-based eye movement interaction and the unique controller interaction of virtual reality system, a multi-sensory multi-input collaborative interaction method is accomplished. The method realizes the robot joints driving of users using multiple interaction methods simultaneously, simplifies the robot programming and control procedure, and optimizes the operation experience. Tests demonstrate that the system is capable of effectively providing monitoring, teleoperation and programming services for remote interaction of robots.

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Section: Interactive Methodsmentioning

confidence: 99%

Data and model hybrid-driven virtual reality robot operating system

Liu

Lin²,

Lin³

et al. 2022

Front. Energy Res.

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“…Visual object tracking is one of the fundamental research topics in the computer vision community, with a plethora of practical applications in areas including autonomous driving [1], intelligent video monitoring [2,3], human-computer interaction [4], and trajectory prediction [5,6]. The general object tracking task is, given the initial state (e.g., central position and extent) of a target in the first frame in an image sequence, to automatically estimate the target's state in the subsequent frames [7,8].…”

Section: Introductionmentioning

confidence: 99%

A Novel Anti-Drift Visual Object Tracking Algorithm Based on Sparse Response and Adaptive Spatial-Temporal Context-Aware

Liu

et al. 2021

Remote Sensing

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Correlation filter (CF) based trackers have gained significant attention in the field of visual single-object tracking, owing to their favorable performance and high efficiency; however, existing trackers still suffer from model drift caused by boundary effects and filter degradation. In visual tracking, long-term occlusion and large appearance variations easily cause model degradation. To remedy these drawbacks, we propose a sparse adaptive spatial-temporal context-aware method that effectively avoids model drift. Specifically, a global context is explicitly incorporated into the correlation filter to mitigate boundary effects. Subsequently, an adaptive temporal regularization constraint is adopted in the filter training stage to avoid model degradation. Meanwhile, a sparse response constraint is introduced to reduce the risk of further model drift. Furthermore, we apply the alternating direction multiplier method (ADMM) to derive a closed-solution of the object function with a low computational cost. In addition, an updating scheme based on the APCE-pool and Peak-pool is proposed to reveal the tracking condition and ensure updates of the target’s appearance model with high-confidence. The Kalam filter is adopted to track the target when the appearance model is persistently unreliable and abnormality occurs. Finally, extensive experimental results on OTB-2013, OTB-2015 and VOT2018 datasets show that our proposed tracker performs favorably against several state-of-the-art trackers.

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Human Computer Interaction System Using Eye-Tracking Features

Cited by 2 publications

References 13 publications

Data and model hybrid-driven virtual reality robot operating system

Data and model hybrid-driven virtual reality robot operating system

A Novel Anti-Drift Visual Object Tracking Algorithm Based on Sparse Response and Adaptive Spatial-Temporal Context-Aware

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