Efficient and Accurate Semi-Automatic Neuron Tracing with Extended Reality.

Neuron tracing, alternately referred to as neuron reconstruction, is the procedure for extracting the digital representation of the three-dimensional neuronal morphology from stacks of microscopic images. Achieving accurate neuron tracing is critical for profiling the neuroanatomical structure at single-cell level and analyzing the neuronal circuits and projections at whole-brain scale. However, the process often demands substantial human involvement and represents a nontrivial task.

Exploring angular-steering illumination-based eyebox expansion for holographic displays.

Holography represents an enabling technology for next-generation virtual and augmented reality systems. However, it remains challenging to achieve both wide field of view and large eyebox at the same time for holographic near-eye displays, mainly due to the essential étendue limitation of existing hardware. In this work, we present an approach to expanding the eyebox for holographic displays without compromising their underlying field of view.

IEEE ISMAR 2022 Report: Toward Better Mixed Realities.

On October 21, 2022, the 21st IEEE International Symposium on Mixed and Augmented Reality (ISMAR 2022) was successfully completed in Singapore. ISMAR is the leading international conference in the fields of augmented reality, mixed reality, and virtual reality. This was the first time that ISMAR was held in Southeast Asia and the first time in hybrid mode.

Investigating learning-empowered hologram generation for holographic displays with ill-tuned hardware.

Existing computational holographic displays often suffer from limited reconstruction image quality mainly due to ill-conditioned optics hardware and hologram generation software. In this Letter, we develop an end-to-end hardware-in-the-loop approach toward high-quality hologram generation for holographic displays. Unlike other hologram generation methods using ideal wave propagation, ours can reduce artifacts introduced by both the light propagation model and the hardware setup, in particular non-uniform illumination.

A gamified augmented reality vocational training program for adults with intellectual and developmental disabilities: A pilot study on acceptability and effectiveness.

Objectives: The Augmented Reality Games to Enhance Vocational Ability of Patients (REAP) was an augmented reality vocational training program that provided skills training in the context of a psychiatric rehabilitation program. It was implemented over 10 weeks and consisted of gamified augmented reality café training scenarios and bridging group activities to facilitate transfer of learning to the work context. This pilot study aimed to explore the acceptability and effectiveness of the REAP program when carried out with adults with intellectual and developmental disabilities attending work therapy.