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Non-Photorealistic Computer Graphics: Modeling, Rendering, and Animation

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Even as developments in photorealistic computer graphics continue to affect our work and leisure activities, practitioners and researchers are devoting more and more attention to non-photorealistic (NPR) techniques for generating images that appear to have been created by hand. These efforts benefit every field in which illustrations--thanks to their ability to clarify, em Even as developments in photorealistic computer graphics continue to affect our work and leisure activities, practitioners and researchers are devoting more and more attention to non-photorealistic (NPR) techniques for generating images that appear to have been created by hand. These efforts benefit every field in which illustrations--thanks to their ability to clarify, emphasize, and convey very precise meanings--offer advantages over photographs. These fields include medicine, architecture, entertainment, education, geography, publishing, and visualization. Non-Photorealistic Computer Graphics is the first and only resource to examine non-photorealistic efforts in depth, providing detailed accounts of the major algorithms, as well as the background information and implementation advice readers need to make headway with these increasingly important techniques. Already, an estimated 10% of computer graphics users require some form of non-photorealism. Strothotte and Schlechtweg's important new book is designed and destined to be the standard NPR reference for this large, diverse, and growing group of professionals.


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Even as developments in photorealistic computer graphics continue to affect our work and leisure activities, practitioners and researchers are devoting more and more attention to non-photorealistic (NPR) techniques for generating images that appear to have been created by hand. These efforts benefit every field in which illustrations--thanks to their ability to clarify, em Even as developments in photorealistic computer graphics continue to affect our work and leisure activities, practitioners and researchers are devoting more and more attention to non-photorealistic (NPR) techniques for generating images that appear to have been created by hand. These efforts benefit every field in which illustrations--thanks to their ability to clarify, emphasize, and convey very precise meanings--offer advantages over photographs. These fields include medicine, architecture, entertainment, education, geography, publishing, and visualization. Non-Photorealistic Computer Graphics is the first and only resource to examine non-photorealistic efforts in depth, providing detailed accounts of the major algorithms, as well as the background information and implementation advice readers need to make headway with these increasingly important techniques. Already, an estimated 10% of computer graphics users require some form of non-photorealism. Strothotte and Schlechtweg's important new book is designed and destined to be the standard NPR reference for this large, diverse, and growing group of professionals.

31 review for Non-Photorealistic Computer Graphics: Modeling, Rendering, and Animation

  1. 5 out of 5

    Andrés Granbosque

    Published in early 2000s but still vigent

  2. 4 out of 5

    Patrick McCarthy

  3. 4 out of 5

    Aleks

  4. 5 out of 5

    Antonio Pontes

  5. 4 out of 5

    Risto Saarelma

  6. 5 out of 5

    Adrianus Yoga

  7. 4 out of 5

    Cameron Chamberlain

  8. 4 out of 5

    Nabil

  9. 5 out of 5

    Brian

  10. 5 out of 5

    Jesús

  11. 5 out of 5

    Mike Lambert

  12. 5 out of 5

    Stephanie

  13. 5 out of 5

    Wesen

  14. 4 out of 5

    Wikimedia Italia

  15. 4 out of 5

    Cornel

  16. 4 out of 5

    Orlando

  17. 4 out of 5

    Kevin Cecelski

  18. 5 out of 5

    Nobo-ok

  19. 5 out of 5

    Agito

  20. 5 out of 5

    Eoin Houlihan

  21. 4 out of 5

    Will Ransohoff

  22. 5 out of 5

    Jeff Schilling

  23. 4 out of 5

    Artem Redko

  24. 4 out of 5

    Matthew Littlemore

  25. 4 out of 5

    Alina Gorbunova

  26. 4 out of 5

    Aria

  27. 4 out of 5

    Darius

  28. 4 out of 5

    Alfan Setyawan

  29. 4 out of 5

    Abdulrahman Al Maiman

  30. 4 out of 5

    Jason Baldus

  31. 5 out of 5

    Dang-Khoa Le Tan

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