This paper presents a compact driver circuit with independent pixel-level temperature regulation for thermo-optic based 2D Nanophotonic phased arrays (NPAs) in light detection and ranging (LIDAR) and Virtual Reality (VR) applications. To minimize the interconnection density, the proposed driver unit uses only a single electrical contact to its corresponding NPA pixel for both heating and temperature measurement functions. The driver was fabricated using TSMC 65 nm technology and each unit is realized in an area of$15\ \mu\mathrm{m}\times 15\ \mu\mathrm{m}$. The design enables scalable 3D heterogeneous integration between any tile-based NPA with pixel pitch below$15\ \mu\mathrm{m}$and its electrical control system. The temperature regulation performance of the proposed circuit was characterized by intentionally introducing a ±20% variation to the load resistance to simulate the temperature deviation in the NPA. The measured phase errors are suppressed by the feedback controller to a maximum of$0.07\pi$and an average of$0.02\pi$within the full$2\pi$phase shift operation range.

Holographic displays and computer-generated holography offer a unique opportunity in improving optical resolutions and depth characteristics of near-eye displays. The thermally-modulated Nanopho-tonic Phased Array (NPA), a new type of holographic display, affords several advantages, including integrated light source and higher refresh rates, over other holographic display technologies. However, the thermal phase modulation of the NPA makes it susceptible to the thermal proximity effect where heating one pixel affects the temperature of nearby pixels. Proximity effect correction (PEC) methods have been proposed for 2D Fourier holograms in the far field but not for Fresnel holograms at user-specified depths. Here we extend an existing PEC method for the NPA to Fresnel holograms with phase-only hologram optimization and validate it through computational simulations. Our method is not only effective in correcting the proximity effect for the Fresnel holograms of 2D images at desired depths but can also leverage the fast refresh rate of the NPA to display 3D scenes with time-division multiplexing.

Abstract Algorithms for finger vein recognition methods are generally designed based on greyscale images containing vein distributions, but greyscale inhomogeneities and non‐venous texture structures often adversely affect the recognition results. Besides, the performance of the algorithm when the field of view is reduced has not been studied. Therefore, the aim of this paper is to propose an algorithm based on binary image, so as to minimize the interference of non‐venous factors in the identification process. We use the feature from accelerated segment test algorithm to detect feature points, and use gradient histogram to describe these feature points in a vectorized manner. In addition, we propose the concept of circular matching neighbourhood, and select the matching feature point pairs in this area. Then, the Euclidean distance and the number of correct matching pairs were comprehensively considered to increase the recognition rate of the algorithm. The algorithm was tested on the database of SDU‐MLA, FV‐USM and MMCBNU‐6000. The results show that the algorithm has certain advantages before and after the field of view is reduced. Therefore, this paper not only provides a new idea for finger vein recognition, but also has practical application value for the miniaturization of finger vein acquisition devices.

External ventricular drainage (EVD) is a high-risk medical procedure that involves inserting a catheter inside a patient’s skull, through the brain and into a ventricle, to drain cerebrospinal fluid and thus relieve elevated intracranial pressure. Once the catheter has entered the skull, its tip cannot be seen. The neurosurgeon has to imagine its location inside the cranium and direct it toward the ventricle using only anatomic landmarks. The EVD catheter is thin and thus hard to track using infra-red depth sensors. Traditional optical tracking using fiducial or other markers inevitably changes the shape or weight of the medical instrument. We present an augmented reality system that depicts the catheter for EVD and a new technique to precisely track the catheter inside the skull. Our technique uses a new linear marker detection method that requires minimal changes to the catheter and is well suited for tracking other thin medical devices that require high-precision tracking.

Thermally modulated Nanophotonic Phased Arrays (NPAs) can be used as phase-only holographic displays. Compared to the holographic displays based on Liquid Crystal on Silicon Spatial Light Modulators (LCoS SLMs), NPAs have the advantage of integrated light source and high refresh rate. However, the formation of the desired wavefront requires accurate modulation of the phase which is distorted by the thermal proximity effect. This problem has been largely overlooked and existing approaches to similar problems are either slow or do not provide a good result in the setting of NPAs. We propose two new algorithms based on the iterative phase retrieval algorithm and the proximal algorithm to address this challenge. We have carried out computational simulations to compare and contrast various algorithms in terms of image quality and computational efficiency. This work is going to benefit the research on NPAs and enable the use of large-scale NPAs as holographic displays.

Far peripheral vision (beyond 60° eccentricity) is beginning to be supported in the latest virtual and augmented reality (VR and AR) headsets. This benefits the VR and AR experiences by allowing a greater amount of information to be conveyed, reducing visual clutter, and enabling subtle visual attention management. However, the visual properties of the far periphery are different from those of the central vision, because of the physiological differences between the areas on the visual cortex responsible for the respective vision types. In this paper, we investigate the perception time in the far peripheral vision, specifically the time it takes for a user to perceive a pattern at a high eccentricity. We have characterized the perception time in the far peripheral vision by conducting a user study on 40 participants in which the participants distinguish between two types of patterns displayed at several sizes and at various eccentricities in their field of view. Our results show that at higher eccentricities, participants take longer to perceive a pattern. Based on user study data, we are able to characterize the desired scaling of patterns at higher eccentricities, so that they can be perceived within a similar amount of time as in the central vision.