Performance assessment of a pupil tracking system for adaptive optics retinal imaging

2008 ◽  
Author(s):  
Betul Sahin ◽  
Fabrice Harms ◽  
Barbara Lamory
Keyword(s):  
Performance Assessment ◽  
Adaptive Optics ◽  
Tracking System ◽  
Retinal Imaging ◽  
Pupil Tracking

A pupil tracking system for adaptive optics retinal imaging

2008 ◽  
Author(s):  
Betul Sahin ◽  
Fabrice Harms ◽  
Barbara Lamory ◽  
Laurent Vabre
Keyword(s):  
Adaptive Optics ◽  
Tracking System ◽  
Retinal Imaging ◽  
Pupil Tracking

Retinal imaging system with adaptive optics enhanced with pupil tracking

2011 ◽  
Author(s):  
Betul Sahin ◽  
Barbara Lamory ◽  
Xavier Levecq ◽  
Laurent Vabre ◽  
Chris Dainty
Keyword(s):  
Adaptive Optics ◽  
Imaging System ◽  
Retinal Imaging ◽  
Pupil Tracking

scholarly journals Adaptive optics with pupil tracking for high resolution retinal imaging

2012 ◽  
Vol 3 (2) ◽  
pp. 225 ◽  
Author(s):  
Betul Sahin ◽  
Barbara Lamory ◽  
Xavier Levecq ◽  
Fabrice Harms ◽  
Chris Dainty
Keyword(s):  
High Resolution ◽  
Adaptive Optics ◽  
Retinal Imaging ◽  
Pupil Tracking

scholarly journals Deep-Learning-Based Pupil Center Detection and Tracking Technology for Visible-Light Wearable Gaze Tracking Devices

2021 ◽  
Vol 11 (2) ◽  
pp. 851
Author(s):  
Wei-Liang Ou ◽  
Tzu-Ling Kuo ◽  
Chin-Chieh Chang ◽  
Chih-Peng Fan
Keyword(s):  
Deep Learning ◽  
Visible Light ◽  
Tracking System ◽  
Recall Rate ◽  
Detection Accuracy ◽  
Learning Technology ◽  
Tracking Errors ◽  
Gaze Tracking ◽  
Detection Technology ◽  
Pupil Tracking

In this study, for the application of visible-light wearable eye trackers, a pupil tracking methodology based on deep-learning technology is developed. By applying deep-learning object detection technology based on the You Only Look Once (YOLO) model, the proposed pupil tracking method can effectively estimate and predict the center of the pupil in the visible-light mode. By using the developed YOLOv3-tiny-based model to test the pupil tracking performance, the detection accuracy is as high as 80%, and the recall rate is close to 83%. In addition, the average visible-light pupil tracking errors of the proposed YOLO-based deep-learning design are smaller than 2 pixels for the training mode and 5 pixels for the cross-person test, which are much smaller than those of the previous ellipse fitting design without using deep-learning technology under the same visible-light conditions. After the combination of calibration process, the average gaze tracking errors by the proposed YOLOv3-tiny-based pupil tracking models are smaller than 2.9 and 3.5 degrees at the training and testing modes, respectively, and the proposed visible-light wearable gaze tracking system performs up to 20 frames per second (FPS) on the GPU-based software embedded platform.

Longitudinal chromatic aberration compensation method for dual-wavelength retinal imaging adaptive optics systems

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
沁雨 朱 ◽  
◽  
国庆 韩 ◽  
建涛 彭 ◽  
启龙 饶 ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Retinal Imaging ◽  
Chromatic Aberration ◽  
Compensation Method ◽  
Dual Wavelength

scholarly journals Wavefront sensorless adaptive optics OCT with the DONE algorithm for in vivo human retinal imaging [Invited]

2017 ◽  
Vol 8 (4) ◽  
pp. 2261 ◽  
Author(s):  
Hans R. G. W. Verstraete ◽  
Morgan Heisler ◽  
Myeong Jin Ju ◽  
Daniel Wahl ◽  
Laurens Bliek ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Retinal Imaging

Bimorph Deformable Mirrors for Adaptive Optics of Human Retinal Imaging System

2013 ◽  
Vol 33 (2) ◽  
pp. 0211001 ◽  
Author(s):  
周虹 Zhou Hong ◽  
官春林 Guan Chunlin ◽  
戴云 Dai Yun
Keyword(s):  
Adaptive Optics ◽  
Imaging System ◽  
Retinal Imaging ◽  
Deformable Mirrors

Research on Flat Field Correction Method in Adaptive Optics Retinal Imaging System

2011 ◽  
Vol 31 (12) ◽  
pp. 1211001 ◽  
Author(s):  
孔宁宁 Kong Ningning ◽  
李抄 Li Chao ◽  
夏明亮 Xia Mingliang ◽  
齐岳 Qi Yue ◽  
李大禹 Li Dayu ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Imaging System ◽  
Retinal Imaging ◽  
Correction Method ◽  
Flat Field

Design of two degree-of-freedom head prop in adaptive optics retinal imaging system

2015 ◽  
Vol 30 (4) ◽  
pp. 590-595
Author(s):  
潘宇骏 PAN Yu-jun ◽  
韩玉琢 HAN Yu-zhuo ◽  
解洪升 XIE Hong-sheng ◽  
杨乐宝 YANG Le-bao ◽  
王少鑫 WANG Shao-xin ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Imaging System ◽  
Retinal Imaging ◽  
Degree Of Freedom ◽  
Two Degree Of Freedom
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