Automatic Location of Landmarks used in Manual Anthropometry
Automatic Location of Landmarks used in Manual Anthropometry
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DOI：
10.2312/3dor.20141055
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发表时间：
2014-04
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通讯作者：
Andrea Giachetti;E. Mazzi;Francesco Piscitelli;Masaki Aono;A. Hamza;Thomas Bonis;Peter Claes;A. Godil;Chunyuan Li;M. Ovsjanikov;Viorica Patraucean;Chang Shu;J. Snyders;P. Suetens;A. Tatsuma;D. Vandermeulen;Stefanie Wuhrer;Pengcheng Xi
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文献类型：
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作者：
Andrea Giachetti;E. Mazzi;Francesco Piscitelli;Masaki Aono;A. Hamza;Thomas Bonis;Peter Claes;A. Godil;Chunyuan Li;M. Ovsjanikov;Viorica Patraucean;Chang Shu;J. Snyders;P. Suetens;A. Tatsuma;D. Vandermeulen;Stefanie Wuhrer;Pengcheng Xi
在这篇文章中，我们报告了SHREC 2014年关于人工人体测量中使用的地标自动定位的结果。该轨道的组织是为了测试现代计算几何/模式识别技术精确定位用于基于磁带的测量的参考点的能力。参与者必须在用结构光体扫描仪获取的人体模型上定位六个特定的地标。提供了一个由50个模型组成的训练集，其中带有对应地标位置的手动注释，以训练算法。还提供了一个包含50个不同模型的测试集，没有注释。通过计算检测点与人工放置点的测地距离以及评估不同的质量分数和功能来测试自动定位方法的准确性。
In this paper we report the results of the SHREC 2014 track on automatic location of landmarks used in manual anthropometry. The track has been organized to test the ability of modern computational geometry/pattern recognition techniques to locate accurately reference points used for tape based measurement. Participants had to locate six specific landmarks on human models acquired with a structured light body scanner. A training set of 50 models with manual annotations of the corresponding landmarks location was provided to train the algorithms. A test set of 50 different models was also provided, without annotations. Accuracy of the automatic location methods was tested via computing geodesic distances of the detected points from manually placed ones and evaluating different quality scores and functions.