测试医用光照下人脸关键点检测精度，提升手术场景定位可靠性。
Evaluation of facial landmark localization performance in a surgical setting
- 用机械臂自动调节位置，固定光源与假人测试面部关键点检测。
- 在大偏航角和俯仰角下，检测准确率显著提升。
- 适用于需高精度定位的神经外科、整形外科等手术场景。
机器人、计算机视觉及其应用在医学领域日益普及。许多面部检测算法已用于神经外科、眼科和整形外科。使用这些算法的常见挑战是光照条件变化及检测位置灵活性不足，难以精准定位患者。本实验在受控环境下测试MediaPipe算法在面部关键点检测的表现，采用机械臂自动调节位置，同时保持手术灯和假人位置固定。结果显示，在手术光照条件下，面部关键点检测精度提升显著，尤其在大偏航角和俯仰角情况下表现更优。标准差/离散度增加源于部分面部关键点检测不准确。该分析为将MediaPipe算法集成至医疗程序提供了依据。
原文摘要 · Abstract (English)
The use of robotics, computer vision, and their applications is becoming increasingly widespread in various fields, including medicine. Many face detection algorithms have found applications in neurosurgery, ophthalmology, and plastic surgery. A common challenge in using these algorithms is variable lighting conditions and the flexibility of detection positions to identify and precisely localize patients. The proposed experiment tests the MediaPipe algorithm for detecting facial landmarks in a controlled setting, using a robotic arm that automatically adjusts positions while the surgical light and the phantom remain in a fixed position. The results of this study demonstrate that the improved accuracy of facial landmark detection under surgical lighting significantly enhances the detection performance at larger yaw and pitch angles. The increase in standard deviation/dispersion occurs due to imprecise detection of selected facial landmarks. This analysis allows for a discussion on the potential integration of the MediaPipe algorithm into medical procedures.
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