Introduction of Learning Techniques for Creating Solid Models from Sketches Including Curves

Masaji Tanaka, Yuki Takamiya, Naoki Tsubota, Shigeo Asanuma

Inductive Learning, IFOG, Sketch, Solid Model
Since several years, the authors have developed a method to automatically convert sketches as 2D line drawings including curved lines into 3D models. However, it was difficult and time consuming to develop the experimental system of the method because various kinds of geometric pattern matching
processes had to be programmed. On the other hand, since decades, machine learning techniques have been developing very quickly. Since the techniques are effective for pattern recognitions in general and the method often uses pattern matching of geometric elements, we apply our inductive learning
techniques to the method in our new method proposed in this paper. Although huge amount of properties of geometric elements would be handled to use the learning techniques, our IFOG technique would prevent the exponential increase of the properties. As the result, the handling of 2D or 3D geometric elements could become clearer and more humanized sketches could be applied in this method.
CAD’16
Introduction of Learning Techniques for Creating Solid Models from Sketches Including Curves

Proceedings of CAD’16

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