Zhao Ying, Geng Xiulin, Li Qi, Jiang Guangqi, Gu Yu, Lv Xiaoqi
School of Information Engineering, University of Science and Technology, Baotou, China.
School of Computer Engineering and Science, Shanghai University, Shanghai, China.
Front Bioeng Biotechnol. 2017 Oct 10;5:58. doi: 10.3389/fbioe.2017.00058. eCollection 2017.
In order to effectively aid the blind with optimal low-resolution vision and visual recovery training, pathfinding and recognition tests were performed using a simulated visual prosthetic scene. Simple and complex virtual scenes were built using 3DMAX and Unity, and pixelated to three different resolutions (32 × 32, 64 × 64, and 128 × 128) for real-time pixel processing. Twenty subjects were recruited to complete the pathfinding and object recognition tasks within the scene. The recognition accuracy and time required were recorded and analyzed after the trials. In the simple simulated prosthetic vision (SPV) scene, when the resolution was increased from 32 × 32 to 48 × 48, the object recognition time decreased from 92.19 ± 6.97 to 43.05 ± 6.08 s, and the recognition accuracy increased from 51.22 ± 8.53 to 85.52 ± 4.93%. Furthermore, the number of collisions decreased from 10.00 ± 2.31 to 3.00 ± 0.68. When the resolution was increased from 48 × 48 to 64 × 64, the object recognition time further decreased from 43.05 ± 6.08 to 19.46 ± 3.71 s, the recognition accuracy increased from 85.52 ± 4.93 to 96.89 ± 2.06%, and the number of collisions decreased from 3.00 ± 0.68 to 1.00 ± 0.29. In complex scenes, the time required to recognize the room type decreased from 115.00 ± 23.02 to 68.25 ± 17.23 s, and object recognition accuracy increased from 65.69 ± 9.61 to 80.42 ± 7.70% when the resolution increased from 48 × 48 to 64 × 64. When the resolution increased from 64 × 64 to 128 × 128, the time required to recognize the room type decreased from 68.25 ± 17.23 to 44.88 ± 9.94 s, and object recognition accuracy increased from 80.42 ± 7.71 to 85.69 ± 7.39%. Therefore, one can conclude that there are correlations between pathfinding and recognition. When the resolution increased, the time required for recognition decreased, the recognition accuracy increased, and the number of collisions decreased. Although the subjects could partially complete the recognition task at a resolution of 32 × 32, the recognition time was too long and recognition accuracy was not good enough to identify simple scenes. Complex scenes required a resolution of at least 48 × 48 for complete recognition. In addition, increasing the resolution shortened the time required to identify the type of room, and improved the recognition accuracy.
为了有效地帮助视力最佳但分辨率较低的盲人以及进行视觉恢复训练，使用模拟视觉假体场景进行了寻路和识别测试。使用3DMAX和Unity构建简单和复杂的虚拟场景，并将其像素化到三种不同的分辨率（32×32、64×64和128×128），以进行实时像素处理。招募了20名受试者在场景中完成寻路和目标识别任务。试验后记录并分析识别准确率和所需时间。在简单模拟假体视觉（SPV）场景中，当分辨率从32×32提高到48×48时，目标识别时间从92.19±6.97秒降至43.05±6.08秒，识别准确率从51.22±8.53%提高到85.52±4.93%。此外，碰撞次数从10.00±2.31降至3.00±0.68。当分辨率从48×48提高到64×64时，目标识别时间进一步从43.05±6.08秒降至19.46±3.71秒，识别准确率从85.52±4.93%提高到96.89±2.06%，碰撞次数从3.00±0.68降至1.00±0.29。在复杂场景中，当分辨率从48×48提高到64×64时，识别房间类型所需时间从115.00±23.02秒降至68.25±17.23秒，目标识别准确率从65.69±9.61%提高到80.42±7.70%。当分辨率从64×64提高到128×128时，识别房间类型所需时间从68.25±17.23秒降至44.88±9.94秒，目标识别准确率从80.42±7.71%提高到85.69±7.39%。因此，可以得出结论，寻路和识别之间存在相关性。当分辨率提高时，识别所需时间减少，识别准确率提高，碰撞次数减少。尽管受试者在32×32的分辨率下可以部分完成识别任务，但识别时间过长，识别准确率不足以识别简单场景。复杂场景至少需要48×48的分辨率才能完全识别。此外，提高分辨率缩短了识别房间类型所需的时间，并提高了识别准确率。
