Handbook Of Sketch based Modeling For Engineering Design: A Practical Approach With Refer

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Bol Handbook of Sketch-Based Modeling for Engineering Design offers a hands-on introduction to Sketch-Based Modeling (SBM) through the use of a custom software application called REFER, which is accessible on GitHub. It presents both a critical perspective on current trends and a constructive framework for developing the next-generation of hybrid SBM methods that combine human-like perceptual insight, classical rigor, and AI scalability.Sketch-Based Modeling (SBM) can be placed at the intersection of two traditions: the classical approach, rooted in decades of accumulated computational and geometric expertise, and the artificial intelligence (AI) approach, powered by massive data and computing resources. Rather than competing, these paradigms can (and should) be used together in a complementary, synergistic manner.Beyond practical instruction, the book discusses how procedural modeling, graph-based methods, and established CAD principles can inform the training of AI systems and provide a pathway toward more robust and scalable SBM solutions. Through concrete examples and source code discussions, readers are introduced to feature detection, deconstruction, and reconstruction of sketches into procedural 3D models, as well as the challenges of working with imperfect input and capturing design intent.

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Handbook of Sketch-Based Modeling for Engineering Design offers a hands-on introduction to Sketch-Based Modeling (SBM) through the use of a custom software application called REFER, which is accessible on GitHub. It presents both a critical perspective on current trends and a constructive framework for developing the next-generation of hybrid SBM methods that combine human-like perceptual insight, classical rigor, and AI scalability.Sketch-Based Modeling (SBM) can be placed at the intersection of two traditions: the classical approach, rooted in decades of accumulated computational and geometric expertise, and the artificial intelligence (AI) approach, powered by massive data and computing resources. Rather than competing, these paradigms can (and should) be used together in a complementary, synergistic manner.Beyond practical instruction, the book discusses how procedural modeling, graph-based methods, and established CAD principles can inform the training of AI systems and provide a pathway toward more robust and scalable SBM solutions. Through concrete examples and source code discussions, readers are introduced to feature detection, deconstruction, and reconstruction of sketches into procedural 3D models, as well as the challenges of working with imperfect input and capturing design intent.


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Merk World Scientific
EAN
  • 9789819825653
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