Research on the method of repairing optical scanning incomplete model based on three-dimensional auricle template

doi:10.11996/JG.j.2095-302X.2025040889

Abstract

Abstract:

Three-dimensional models of the human auricle are essential for ergonomics and numerical simulation. Optical scanning imaging enables fast modeling, but local recessed structures, such as the cavum concha, cannot reflect light back to the scanning device, resulting in scanning blind spots. Traditional methods use reverse-engineering software to patch these areas based on the curvature of surrounding triangular meshes; however, the accuracy is relatively low and the efficiency is not high. To enhance the model accuracy, ear impression material can be injected into the cavum concha, and the resulting ear impression model is then scanned to obtain the precise recessed structure. This model is manually aligned and globally registered with the auricle scanning model at their overlapping regions to generate a relatively accurate and complete model. However, the overall process is complex and time-consuming. To address this issue, a method based on a three-dimensional auricle template to repair optical scanning incomplete models was proposed. First, the method constructed a statistical shape model library based on accurate complete models from 35 adult subjects and generated templates based on their correlated features. Then, an improved MeshMonk program was employed to rigidly and non-rigidly register the templates to the incomplete models of 5 new subjects to generate complete models. Finally, the root mean square (RMS) of deviation distances was used to compare and analyze the geometric differences among the repaired complete model, the generated complete model, and the accurate complete model for five subjects. The results indicated that the RMS error between the generated complete model and the accurate complete model was (0.37±0.01) mm (within the acceptable threshold of 0.50 mm). For point clouds with distances exceeding 0.50 mm, the RMS error between the generated complete model and the accurate complete model was (0.93±0.12) mm, smaller than the RMS error between the repaired complete model and the accurate complete model (2.87±0.49) mm. This demonstrated that the proposed method improved accuracy by approximately 68% compared to the reverse engineering software repair method when the point cloud distance exceeded 0.50 mm. Moreover, the method was streamlined and efficient, suggesting applicability for 3D scanning and modeling of the entire auricle or even the head.

Key words: optical scanning, incomplete model, 3D auricle template, model registration, accuracy comparison

CLC Number:

LIN Zhiyuan, WANG Yewei, YU Guangzheng, LI Zhelin, ZHANG Xin. Research on the method of repairing optical scanning incomplete model based on three-dimensional auricle template[J]. Journal of Graphics, 2025, 46(4): 889-898.

Figures/Tables 13

Table 1 3D scanner and related parameters

参数	扫描仪
参数	手持式	桌面级
商品名称	Reeyee Pro 2X	Reeyee
光源	三色LED	白光LED
扫描范围	360°	360°
精度/mm	0.1	0.1
分辨率/mm	0.50，1.00，1.50	0.17~0.20
配套软件	Reeyee Pro_v3.4.0.1	Reeyee_v2.7.1.0
输出格式	OBJ，STL，PLY	OBJ，STL，PLY

Fig. 1 Acquisition process of MaC

Fig. 2 Partial process of creating a three-dimensional auricle template ((a) Align to the global coordinate system; (b) Auricle extraction results)

Fig. 3 Three-dimensional auricle template

Fig. 4 Schematic diagram of the MeshMonk surface registration algorithm

Fig. 5 Landmark points for auricle registration ((a) MiC; (b) Mtemp)

Fig. 6 The process of repairing the auricular incomplete model by three-dimensional auricular template method

Fig. 7 Surface morphologies of MiC after treatment by three methods ((a) Incomplete model; (b) Software patching method; (c) Template registration method; (d) Ear print compensation method)

Fig. 8 Distance color scale diagram of MgC, MrC and MaC ((a) MgC-MgC; (b) MrC-MgC)

Table 2 Comparison of root mean square values between MgC and MrC

受试者	生成完整模型/mm	修补完整模型/mm
1	0.36	0.54
2	0.38	0.54
3	0.38	0.56
4	0.36	0.48
5	0.37	0.36
均值±标准差	0.37±0.01^a	0.50±0.08^a

Fig. 9 Point cloud distance frequency histograms of MgC and MaC, MrC and MaC ((a) ≤-0.5 mm; (b) ≥0.5 mm)

Table 3 Comparison of root mean square values between MgC and MrC

受试者	生成完整模型/mm	修补完整模型/mm
1	0.76	2.88
2	1.02	2.23
3	0.84	3.41
4	1.03	3.28
5	1.01	2.54
均值±标准差	0.93±0.12^a	2.87±0.49^a

Fig. 10 Box plot of root mean square error values

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