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1. Low-Profile Induced-Voltage Distance Ranger for Smart Contact Lenses

   https://doi.org/10.1109/TBME.2020.3040161  

   Ghosh, Chayanjit; Mastrangelo, Alex; Karkhanis, Mohit Uday; Deshpande, Adwait P.; Banerjee, Aishwaryadev; Kim, Hanseup; Mastrangelo, Carlos (November 2020, IEEE Transactions on Biomedical Engineering)

   null (Ed.)

   Objective: We present a novel, low-profile, scleral-coil based, distance ranging system which is suitable for smart, accommodating contact lenses. Methods: We measure the induced emf between a set of four thin semi-circular coils patterned on flexible Kapton substrates that conform to the eyes’ sclera. This induced emf is a function of eye gaze angles. The distance from the eyes to the desired object is next determined via the triangulation of the eye gaze angles Results: Experiments on simulated tissue gel eyeballs indicate an accurate prediction of object distance in the 0.1-15 D (diopter) range with a 0.15 D RMS error and object direction in the -15 to 15-degree field of view with 0.4-degree RMS error, respectively. The energy required per range reading was determined to be as low as 20 μJ. Conclusion: Experimental data shows that the distance ranging system can accurately measure eye-gaze angles and object-distance with very low energy consumption. Significance: The high-accuracy, low-profile and reduced energy requirements make the distance ranger suitable for low-power vision corrective applications such as smart contact lenses. 

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2. Estimating Perceptual Depth Changes with Eye Vergence and Interpupillary Distance using an Eye Tracker in Virtual Reality

   https://doi.org/10.1145/3517031.3529632  

   Arefin, Mohammed Safayet; Swan II, J. Edward; Cohen Hoffing, Russell A.; Thurman, Steven M. (June 2022, ACM Symposium on Eye Tracking Research and Applications)

   Blascheck, Tanja; Bradshaw, Jessica; Vrzakova, Hana (Ed.)

   Virtual Reality (VR) technology has advanced to include eye-tracking, allowing novel research, such as investigating how our visual system coordinates eye movements with changes in perceptual depth. The purpose of this study was to examine whether eye tracking could track perceptual depth changes during a visual discrimination task. We derived two depth-dependent variables from eye tracker data: eye vergence angle (EVA) and interpupillary distance (IPD). As hypothesized, our results revealed that shifting gaze from near-to-far depth significantly decreased EVA and increased IPD, while the opposite pattern was observed while shifting from far-to-near. Importantly, the amount of change in these variables tracked closely with relative changes in perceptual depth, and supported the hypothesis that eye tracker data may be used to infer real-time changes in perceptual depth in VR. Our method could be used as a new tool to adaptively render information based on depth and improve the VR user experience. 

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3. Fast Light-Weight Near-Field Photometric Stereo

   Daniel Lichy, Soumyadip Sengupta (July 2022, IEEE Conference on Computer Vision and Pattern Recognition)

   We introduce the first end-to-end learning-based solution to near-field Photometric Stereo (PS), where the light sources are close to the object of interest. This setup is especially useful for reconstructing large immobile objects. Our method is fast, producing a mesh from 52 512x384 resolution images in about 1 second on a commodity GPU, thus potentially unlocking several AR/VR applications. Existing approaches rely on optimization coupled with a far-field PS network operating on pixels or small patches. Using optimization makes these approaches slow and memory intensive (requiring 17GB GPU and 27GB of CPU memory) while using only pixels or patches makes them highly susceptible to noise and calibration errors. To address these issues, we develop a recursive multi-resolution scheme to estimate surface normal and depth maps of the whole image at each step. The predicted depth map at each scale is then used to estimate 'per-pixel lighting' for the next scale. This design makes our approach almost 45x faster and 2 degrees more accurate (11.3 vs. 13.3 degrees Mean Angular Error) than the state-of-the-art near-field PS reconstruction technique, which uses iterative optimization. 

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4. Improved vergence and accommodation via Purkinje Image tracking with multiple cameras for AR glasses

   https://doi.org/10.1109/ISMAR50242.2020.00058  

   Lu, Conny; Chakravarthula, Praneeth; Tao, Yujie; Chen, Steven; Fuchs, Henry (November 2020, 2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR))

   null (Ed.)

   We present a personalized, comprehensive eye-tracking solution based on tracking higher-order Purkinje images, suited explicitly for eyeglasses-style AR and VR displays. Existing eye-tracking systems for near-eye applications are typically designed to work for an on-axis configuration and rely on pupil center and corneal reflections (PCCR) to estimate gaze with an accuracy of only about 0.5°to 1°. These are often expensive, bulky in form factor, and fail to estimate monocular accommodation, which is crucial for focus adjustment within the AR glasses. Our system independently measures the binocular vergence and monocular accommodation using higher-order Purkinje reflections from the eye, extending the PCCR based methods. We demonstrate that these reflections are sensitive to both gaze rotation and lens accommodation and model the Purkinje images’ behavior in simulation. We also design and fabricate a user-customized eye tracker using cheap off-the-shelf cameras and LEDs. We use an end-to-end convolutional neural network (CNN) for calibrating the eye tracker for the individual user, allowing for robust and simultaneous estimation of vergence and accommodation. Experimental results show that our solution, specifically catering to individual users, outperforms state-of-the-art methods for vergence and depth estimation, achieving an accuracy of 0.3782°and 1.108 cm respectively. 

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5. Evolution of anisotropic turbulence in the fast and slow solar wind: Theory and Solar Orbiter measurements

   https://doi.org/10.1051/0004-6361/202140672  

   Adhikari, L.; Zank, G. P.; Zhao, L.-L.; Telloni, D.; Horbury, T. S.; O’Brien, H.; Evans, V.; Angelini, V.; Owen, C. J.; Louarn, P.; et al (December 2021, Astronomy & Astrophysics)

   Aims. Solar Orbiter (SolO) was launched on February 9, 2020, allowing us to study the nature of turbulence in the inner heliopshere. We investigate the evolution of anisotropic turbulence in the fast and slow solar wind in the inner heliosphere using the nearly incompressible magnetohydrodynamic (NI MHD) turbulence model and SolO measurements. Methods. We calculated the two dimensional (2D) and the slab variances of the energy in forward and backward propagating modes, the fluctuating magnetic energy, the fluctuating kinetic energy, the normalized residual energy, and the normalized cross-helicity as a function of the angle between the mean solar wind speed and the mean magnetic field ( θ UB ), and as a function of the heliocentric distance using SolO measurements. We compared the observed results and the theoretical results of the NI MHD turbulence model as a function of the heliocentric distance. Results. The results show that the ratio of 2D energy and slab energy of forward and backward propagating modes, magnetic field fluctuations, and kinetic energy fluctuations increases as the angle between the mean solar wind flow and the mean magnetic field increases from θ UB  = 0° to approximately θ UB  = 90° and then decreases as θ UB  → 180°. We find that solar wind turbulence is a superposition of the dominant 2D component and a minority slab component as a function of the heliocentric distance. We find excellent agreement between the theoretical results and observed results as a function of the heliocentric distance. 

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