Abstract
The purpose of this study is to identify objects by semi-supervised learning based on clustering of 3D point cloud obtained by a laser scanner. In this study, by identifying general name of the object, reducing labor of creating learned data for the identification is contrived. Conventionally, a discriminator is manually trained by presenting each target object together with a corresponding label one by one. If the number of object to be learned becomes larger. labor for training the discriminator increases. Therefore, manual training is avoided and training method reducing the labor is proposed in this paper.
