Analyses and Visualization of Characteristics of Car Body Types by Using Convolutional Neural Network

S. Tanaka, Toshinobu Harada, Kenji Ono
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引用次数: 1

Abstract

: The cars are classified by cars’ body types. However the characteristics are basically similar at first sight, so it is difficult to distinguish the differences among those cars’ body types. Therefore, in this study, we considered that cars’ characteristics could be analyzed by using deep learning and image recognition technology, developed a system to visualize the judgment and characteristic parts of cars’ body types. Specifically, we made renderings of the CG model of 30 cars by setting 360 viewpoints in 1 degree increments around each car. Deep learning was performed using these 2D images as teacher signals. The car body type recognition probability of each angle is graphed, and the characteristic parts of each car body type are visualized. As a result, we clarified the visual angles and the pars contributing the judgment of cars’ body types.
基于卷积神经网络的车体类型特征分析与可视化
这些车是按车体类型分类的。然而,这些车型的特征乍一看基本相似,因此很难区分这些车型之间的差异。因此,在本研究中,我们认为可以通过深度学习和图像识别技术来分析汽车的特征,开发了一个系统来可视化汽车车身类型的判断和特征部件。具体来说,我们制作了30辆汽车的CG模型的渲染图,每辆车周围以1度的增量设置360个视点。使用这些二维图像作为教师信号进行深度学习。绘制了各角度的车体类型识别概率图,并对各车体类型的特征部件进行了可视化。因此,我们明确了视角和有助于判断汽车车身类型的部分。
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