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首页> 外文期刊>Arabian Journal for Science and Engineering >Automated Fiducial Points Detection Using Human Body Segmentation
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Automated Fiducial Points Detection Using Human Body Segmentation

机译：使用人体分割的自动基准点检测

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摘要

Accurately detected human body fiducial points provide an easy and efficient method for human body posture analysis and the extraction of anthropometric parameters. In the proposed work, an efficient algorithm for automated and accurate detection of fiducial points is developed for both the frontal and the lateral images. An algorithm for automatic human body segmentation of the frontal image is also developed using automatically detected set of primary fiducial points. Additional fiducial points are obtained by applying peak and valley algorithm on the silhouettes of each segment. The detection accuracy of the automatically detected fiducial points is calculated by comparing their locations with the manually marked fiducial points. The proposed algorithm is tested on 45 subjects including both male and female genders and variable Body Mass Indexes. In most cases, the algorithm successfully detects seventy fiducial points for each subject in the testing set. A quantitative analysis of the error in the position of the detected fiducial points shows that the algorithm performs better than the state-of-the-art algorithms found in the existing literature. In the evaluation of the algorithm, the percentage accuracy of the detected fiducial points is calculated and it is observed that the proposed algorithm performs better for the majority of the fiducial points.
机译：准确检测到的人体基准点为人体姿势分析和人体测量参数的提取提供了一种简单有效的方法。在提出的工作中，为正面和侧面图像开发了一种自动且准确地检测基准点的有效算法。还使用自动检测的一组主要基准点开发了一种用于人体正面图像自动分割的算法。通过在每个段的轮廓上应用峰和谷算法，可以获得其他基准点。通过将自动检测的基准点的位置与手动标记的基准点进行比较，可以计算出检测精度。该算法在包括男性和女性以及可变体重指数在内的45个主题上进行了测试。在大多数情况下，该算法可以为测试集中的每个对象成功检测到70个基准点。对检测到的基准点位置误差的定量分析表明，该算法的性能要优于现有文献中的最新算法。在算法评估中，计算了检测到的基准点的百分比准确性，并且观察到该算法对大多数基准点的性能更好。

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