Ebook Download Geometric Transformations for 3D Modeling
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Geometric Transformations for 3D Modeling
Ebook Download Geometric Transformations for 3D Modeling
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About the Author
Michael E. Mortenson writes and does independent research in 3D geometric modeling and computer-aided design. He is a former research scientist with a major aerospace corporation and the author of several highly successful textbooks, including Mathematics for Computer Graphics Applications, Second Edition and Geometric Modeling, Third Edition. Mortenson is a graduate of the UCLA School of Engineering.
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Product details
Hardcover: 380 pages
Publisher: Industrial Press, Inc.; 2 edition (April 1, 2007)
Language: English
ISBN-10: 0831133384
ISBN-13: 978-0831133382
Product Dimensions:
7.3 x 1.1 x 10 inches
Shipping Weight: 2 pounds (View shipping rates and policies)
Average Customer Review:
4.6 out of 5 stars
2 customer reviews
Amazon Best Sellers Rank:
#2,773,652 in Books (See Top 100 in Books)
Excellent Book! Quite readable, and gives historical and practical insights into the mathematics being presented. I am a retired engineer, so I do have some math in my background, and I found the level just right.
Pedagogically, Mortenson's presentation is easy for a reader to follow. Accompanied by generous numbers of diagrams. He gives understandable interpretations of how matrices are used to represent different types of transformations. The underlying geometrical rationale is clear.En route, the reader is gently introduced to group theory. For finite groups. A way to bind geometry and symmetry. Interestingly, the notation he uses for the symmetries and groups is Schonflies. In 1982, this was already being phased out by crystallographers, in favour of International notation. But maybe mathematicians prefer the older style.There is also a quick discussion of tensors. Giving rise to contra and covariant vectors. And the metric tensor is introduced as a key idea. All this is a jumping off point for physicists studying General Relativity, though it is not actually mentioned by name.
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