Background and aim: Most of the Mixed Reality models used in the surgical telepresence are suffering from discrepancies in the boundary area and spatial-temporal inconsistency due to the illumination variation in the video frames. The aim behind this work is to propose a new solution that helps produce the composite video by merging the augmented video of the surgery site and the virtual hand of the remote expertise surgeon. The purpose of the proposed solution is to decrease the processing time and enhance the accuracy of merged video by decreasing the overlay and visualization error and removing occlusion and artefacts. Methodology: The proposed system enhanced the mean value cloning algorithm that helps to maintain the spatial-temporal consistency of the final composite video. The enhanced algorithm includes the 3D mean value coordinates and improvised mean value interpolant in the image cloning process, which helps to reduce the sawtooth, smudging and discolouration artefacts around the blending region. Results: As compared to the state of the art solution, the accuracy in terms of overlay error of the proposed solution is improved from 1.01mm to 0.80mm whereas the accuracy in terms of visualization error is improved from 98.8% to 99.4%. The processing time is reduced to 0.173 seconds from 0.211 seconds. Conclusion: Our solution helps make the object of interest consistent with the light intensity of the target image by adding the space distance that helps maintain the spatial consistency in the final merged video.

中文翻译：

---

在肠道和口腔颌面外科手术远程呈现中使用混合现实的新解决方案：3D均值克隆算法

背景和目的：由于视频帧中的光照变化，外科远程呈现中使用的大多数混合现实模型都存在边界区域差异和时空不一致的问题。这项工作的目的是提出一种新的解决方案，通过合并手术部位的增强视频和远程专业外科医生的虚拟手来帮助制作复合视频。提出的解决方案的目的是通过减少覆盖和可视化错误并消除遮挡和伪影来减少处理时间并提高合并视频的准确性。方法：建议的系统增强了平均值克隆算法，有助于维持最终复合视频的时空一致性。增强的算法在图像克隆过程中包括3D平均值坐标和临时的平均值插值，这有助于减少混合区域周围的锯齿，污迹和变色伪影。结果：与最先进的解决方案相比，所提出的解决方案的覆盖误差精度从1.01mm提高到0.80mm，而可视化误差的精度则从98.8％提高到99.4％。处理时间从0.211秒减少到0.173秒。结论：我们的解决方案通过添加有助于在最终合并视频中保持空间一致性的空间距离，帮助使感兴趣的对象与目标图像的光强度保持一致。混合区域周围的污迹和变色伪影。结果：与最先进的解决方案相比，所提出的解决方案的覆盖误差精度从1.01mm提高到0.80mm，而可视化误差的精度则从98.8％提高到99.4％。处理时间从0.211秒减少到0.173秒。结论：我们的解决方案通过添加有助于在最终合并视频中保持空间一致性的空间距离，帮助使感兴趣的对象与目标图像的光强度保持一致。混合区域周围的污迹和变色伪影。结果：与最先进的解决方案相比，所提出的解决方案的覆盖误差精度从1.01mm提高到0.80mm，而可视化误差的精度则从98.8％提高到99.4％。处理时间从0.211秒减少到0.173秒。结论：我们的解决方案通过添加有助于在最终合并视频中保持空间一致性的空间距离，帮助使感兴趣的对象与目标图像的光强度保持一致。80mm，而可视化误差的准确性从98.8％提高到99.4％。处理时间从0.211秒减少到0.173秒。结论：我们的解决方案通过添加有助于在最终合并视频中保持空间一致性的空间距离，帮助使感兴趣的对象与目标图像的光强度保持一致。80mm，而可视化误差的准确性从98.8％提高到99.4％。处理时间从0.211秒减少到0.173秒。结论：我们的解决方案通过添加有助于在最终合并视频中保持空间一致性的空间距离，帮助使感兴趣的对象与目标图像的光强度保持一致。