The Use of Real-Time Image Stabilization and Augmented Reality Eyewear in the Treatment of Oscillopsia

Objectives/Hypothesis. The symptom of oscillopsia in patients with bilateral vestibular loss (BVL) can be reduced as dynamic visual acuity (DVA), the reduction in visual acuity during head movement, is improved by using real-time image stabilization, delivered by augmented reality eyewear. Setting. Tertiary multidisciplinary neurotology clinic. Study Design. Prospective experimental study. Methods. Immersive virtual reality glasses used in combination with a compact digital video camera were used. A software algorithm was developed that used a center-weighted Lucas-Kanade optical flow method to stabilize video in real time. Six patients with BVL were tested for changes in DVA using the eyewear. The ability to read a Snellen chart during a 2-Hz oscillating head rotation DVA test was measured. Results. For combined scores of vertical and horizontal head rotations, the mean number of lines readable at rest was 7.86, which dropped to 2.77 with head movement (a combination of vertical and horizontal perturbations). This increased to a mean of 6.14 lines with the image stabilization software being activated. This difference was statistically significant ( P < .001). Conclusion. This is the first successful attempt to improve dynamic visual acuity in patients with bilateral vestibular loss. Recent hardware upgrades are promising in improving these results even further.

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Real Time Shadow Mapping for Augmented Reality Photorealistic Rendering

Applied Sciences ◽

10.3390/app9112225 ◽

2019 ◽

Vol 9 (11) ◽

pp. 2225 ◽

Cited By ~ 1

Author(s):

Francesco Osti ◽

Gian Maria Santi ◽

Gianni Caligiana

Keyword(s):

Augmented Reality ◽

Real Time ◽

Real Life ◽

Shadow Mapping ◽

Photorealistic Rendering ◽

Real Time Image ◽

Image Capturing ◽

Microsoft Hololens ◽

The Right ◽

Time Image

In this paper, we present a solution for the photorealistic ambient light render of holograms into dynamic real scenes, in augmented reality applications. Based on Microsoft HoloLens, we achieved this result with an Image Base Lighting (IBL) approach. The real-time image capturing that has been designed is able to automatically locate and position directional lights providing the right illumination to the holograms. We also implemented a negative “shadow drawing” shader that contributes to the final photorealistic and immersive effect of holograms in real life. The main focus of this research was to achieve a superior photorealism through the combination of real-time lights placement and negative “shadow drawing” shader. The solution was evaluated in various Augmented Reality case studies, from classical ones (using Vuforia Toolkit) to innovative applications (using HoloLens).

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Real-Time Image Stabilization Method Based on Optical Flow and Binary Point Feature Matching

Electronics ◽

10.3390/electronics9010198 ◽

2020 ◽

Vol 9 (1) ◽

pp. 198 ◽

Cited By ~ 3

Author(s):

Zilong Deng ◽

Dongxiao Yang ◽

Xiaohu Zhang ◽

Yuguang Dong ◽

Chengbo Liu ◽

...

Keyword(s):

Optical Flow ◽

Real Time ◽

Image Matching ◽

Image Guidance ◽

Feature Matching ◽

Guidance System ◽

Stabilization Method ◽

Image Stabilization ◽

Real Time Image ◽

Time Image

The strap-down missile-borne image guidance system can be easily affected by the unwanted jitters of the motion of the camera, and the subsequent recognition and tracking functions are also influenced, thus severely affecting the navigation accuracy of the image guidance system. So, a real-time image stabilization technology is needed to help improve the image quality of the image guidance system. To satisfy the real-time and accuracy requirements of image stabilization in the strap-down missile-borne image guidance system, an image stabilization method based on optical flow and image matching with binary feature descriptors is proposed. The global motion of consecutive frames is estimated by the pyramid Lucas-Kanade (LK) optical flow algorithm, and the interval frames image matching based on fast retina keypoint (FREAK) algorithm is used to reduce the cumulative trajectory error. A Kalman filter is designed to smooth the trajectory, which is conducive to fitting to the main motion of the guidance system. Simulations have been carried out, and the results show that the proposed algorithm improves the accuracy and real-time performance simultaneously compared to the state-of-art algorithms.

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