School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China.
J Neural Eng. 2018 Apr;15(2):026025. doi: 10.1088/1741-2552/aa966d.
Retinal prosthesis devices have shown great value in restoring some sight for individuals with profoundly impaired vision, but the visual acuity and visual field provided by prostheses greatly limit recipients' visual experience. In this paper, we employ computer vision approaches to seek to expand the perceptible visual field in patients implanted potentially with a high-density retinal prosthesis while maintaining visual acuity as much as possible.
We propose an optimized content-aware image retargeting method, by introducing salient object detection based on color and intensity-difference contrast, aiming to remap important information of a scene into a small visual field and preserve their original scale as much as possible. It may improve prosthetic recipients' perceived visual field and aid in performing some visual tasks (e.g. object detection and object recognition). To verify our method, psychophysical experiments, detecting object number and recognizing objects, are conducted under simulated prosthetic vision. As control, we use three other image retargeting techniques, including Cropping, Scaling, and seam-assisted shrinkability.
Results show that our method outperforms in preserving more key features and has significantly higher recognition accuracy in comparison with other three image retargeting methods under the condition of small visual field and low-resolution.
The proposed method is beneficial to expand the perceived visual field of prosthesis recipients and improve their object detection and recognition performance. It suggests that our method may provide an effective option for image processing module in future high-density retinal implants.
视网膜假体设备在为视力严重受损的个体恢复部分视力方面显示出了巨大的价值,但假体提供的视力和视野极大地限制了接受者的视觉体验。在本文中,我们采用计算机视觉方法,试图在患者植入高密度视网膜假体的情况下扩大可感知的视野,同时尽可能保持视力。
我们提出了一种优化的基于内容感知的图像重定向方法,通过引入基于颜色和强度差对比度的显著目标检测,旨在将场景的重要信息重新映射到小视野中,并尽可能保持其原始比例。它可以提高假体接受者的感知视野,并有助于执行一些视觉任务(例如目标检测和目标识别)。为了验证我们的方法,在模拟假体视觉下进行了物体数量检测和物体识别的心理物理实验。作为对照,我们使用了其他三种图像重定向技术,包括裁剪、缩放和接缝辅助可缩性。
结果表明,与其他三种图像重定向方法相比,我们的方法在小视野和低分辨率条件下能够更好地保留更多的关键特征,并且具有更高的识别准确率。
该方法有利于扩大假体接受者的感知视野,提高他们的目标检测和识别性能。这表明,我们的方法可能为未来高密度视网膜植入物中的图像处理模块提供了一种有效的选择。