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Titlebook: VR Integrated Heritage Recreation; Using Blender and Un Abhishek Kumar Book 2020 Abhishek Kumar 2020 Virtual Reality.Rendering.Texturing.3D

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發(fā)表于 2025-3-21 16:03:57 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱VR Integrated Heritage Recreation
副標(biāo)題Using Blender and Un
編輯Abhishek Kumar
視頻videohttp://file.papertrans.cn/981/980163/980163.mp4
概述Provides an in-depth workflow guide for modeling, texturing, and game engine integration.Shows you how to create game-ready, historically accurate assets and materials.Teaches you how to create a full
圖書封面Titlebook: VR Integrated Heritage Recreation; Using Blender and Un Abhishek Kumar Book 2020 Abhishek Kumar 2020 Virtual Reality.Rendering.Texturing.3D
描述Create assets for history-based games. This book covers the fundamental principles required to understand and create architectural visualizations of historical locations using digital tools. You will explore aspects of 3D design visualization and VR integration using industry-preferred software.?.Some of the most popular video games in recent years have historical settings (Age of Empires, Call of Duty, etc.). Creating these games requires creating historically accurate game assets. You will use Blender to create VR-ready assets by modeling and unwrapping them. And you will use Substance Painter to texture the assets that you create..You will also learn how to use the Quixel Megascans library to acquire and implement physically accurate materials in the scenes. Finally, you will import the assets into Unreal Engine 4 and recreate a VR integrated heritage that can be explored in real time. Using VR technology and game engines,you can digitally recreate historical settings for games..What You Will Learn.Create high-quality, optimized models suitable for any 3D game engine.Master the techniques of texturing assets using Substance Painter and Quixel Megascans.Keep assets historically a
出版日期Book 2020
關(guān)鍵詞Virtual Reality; Rendering; Texturing; 3D; Design visualization; VR integration; UE4; Game engine
版次1
doihttps://doi.org/10.1007/978-1-4842-6077-7
isbn_softcover978-1-4842-6076-0
isbn_ebook978-1-4842-6077-7
copyrightAbhishek Kumar 2020
The information of publication is updating

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Abhishek Kumar the most efficient models. This research also includes the application of a word replacement algorithm to guarantee that abusive words completely lose their destructive context. The research seeks to reduce the negative effects of abusive information and promote a more positive digital environment
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Abhishek Kumarultaneous removal of the users’ protected attributes with continuous and/or categorical values. Our experiments on two datasets,.and., from the music and movie domains, respectively, show that our approach can yield better results than its singular removal counterparts (based on.) in effectively mit
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Abhishek Kumaration on Vietnamese clinical texts, our work aims at an effective novel solution. Different from the existing works, our solution supports a cross-domain context where data shortage and imbalance exist simultaneously in online processing. It defines Nonparametric Self-Training, a parameter-free semi
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Abhishek Kumar identifying related groups to guide monitoring efforts. A decision tree classifier assessed the significance of features in predicting water quality and found ’Fecal coliforms’ to be the most crucial, achieving an accuracy of 99.99%. Additionally, Random Forest, Support Vector Machine, and AdaBoost
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Abhishek Kumarhensive case study is presented that aims at designing an HCAI service to enhance the systematic literature review process in the domain of AI in education. This research contributes significantly to the integration of AI capabilities within service science and provides a methodological framework fo
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