1. 山东农业大学机械与电子工程学院，山东 泰安 271018
2. 山东省农业装备智能化工程实验室，山东 泰安 271018
3. Department of Mechanical Engineering, National University of Singapore, Singapore 117575, Singapore
4. 中国农业大学工学院，北京 100083
3D Model Feature Extraction Based on Light Propagation Simulation with Monte Carlo Method
LIU Hong-hao1, LIU Xian-xi1, ZHANG Kai-xing1,2*, LU Shan1, Lee Heow Pueh3, SONG Zheng-he4
1. College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai’an 271018, China
2. Shandong Provincial Engineering Laboratory of Agricultural Equipment Intelligence，Tai’an 271018，China
3. Department of Mechanical Engineering, National University of Singapore, Singapore 117575, Singapore
4. College of Engineering, China Agricultural University, Beijing 100083, China
Abstract：Three-dimensional model has been showing extensive demand and vitality in modern industrial design, artificial intelligence and software design fields. Traditional feature extraction methods merely depend on model surface feature, which could not sufficiently satisfy complex model feature extraction needs. In order to improve the accuracy of model feature extraction, a 3D model feature extraction method with high discrimination was proposed based on spectral analysis and light propagation attributes. Firstly, the probability of light transmission, scattering and reflection when light propagation in different medium was quantitatively analyzed with scattering coefficient, absorption coefficient and anisotropy parameters. Secondly, the Monte-Carlo method was used to simulate light propagation in complex 3D model, where different feature statistics including angle, distance and energy were obtained to complete feature extraction. Then, the influence factors of photon beam number and constrained space shape were tested for optimal parameters determination. Finally, the feature extraction effectiveness was evaluated on retrieval precision, recall and E-measure. The results showed that the feature extraction accuracy sensitively varied with constrained space shape and the optimal constrained space for photon propagation was sphere; The feature extraction efficiency decreased with more photon beams, and within basic accuracy requirement, 10 000 to 25 000 photon beams were the optimal simulation number; The feature extraction accuracy of proposed method was higher than the wavelet transform, distance-angle and D2 distribution methods, which is more suitable for offline feature extraction of complex 3D models. The proposed simulation method of feature extraction broadens spectral analysis application, which could extract the integrated feature between model surface and internal structure, promoting model feature extraction research.
Key words：Light propagation simulation；Feature extraction；Monte-Carlo method；3D model
刘洪豪，刘贤喜，张开兴，卢 山，Lee Heow Pueh，宋正河. 基于光传播Monte Carlo模拟的三维模型特征提取方法[J]. 光谱学与光谱分析, 2020, 40(02): 385-390.
LIU Hong-hao, LIU Xian-xi, ZHANG Kai-xing, LU Shan, Lee Heow Pueh, SONG Zheng-he. 3D Model Feature Extraction Based on Light Propagation Simulation with Monte Carlo Method. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(02): 385-390.
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