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NPR in the Wild

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Image and Video-Based Artistic Stylisation

Part of the book series: Computational Imaging and Vision ((CIVI,volume 42))

Abstract

During the early years of computer graphics, the results were arguably not as realistic as the intended goal set forth. However, it was not until sometime later that non-realism was accepted as a goal worthwhile pursuing. Since then, NPR has matured considerably and found uses in numerous applications, ranging from movies and television, production tools, and games, to novelty and casual creativity apps on mobile devices. This chapter presents examples from each of these categories within their historical and applied context.

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Notes

  1. 1.

    As such, their work is closer related to physical modeling and simulation than NPR.

  2. 2.

    For technical details on stippling, refer to Chap. 3.

  3. 3.

    Multiple screens, commonly rotated relative to one another and with slightly varying grid spacing, are used to reproduce color photographs.

  4. 4.

    Consumer GPUs only became available in the late 1990s and were limited to a fixed function pipeline. General GPU accelerated image processing operations via fragment shaders were introduced in the OpenGL 2.0 specification, in late 2004.

  5. 5.

    Random and pseudo-random artifacts are a popular NPR mechanism to simulate natural uncertainty or manual jitter. But since such randomness is extrinsic to the scene, special care must be taken to ensure temporal coherence during animation. Consequently, a number of works are dedicated to this topic [5, 6, 24].

  6. 6.

    For pseudo-code of their implementation, refer to NVidia’s “GPU Gems 2” [37], which is also available online.

  7. 7.

    http://www.gotfuturama.com/Information/Articles/3dani.dhtml.

  8. 8.

    http://www.olm.co.jp/rd/technology/tools/?lang=en.

  9. 9.

    Team Fortress 2 (Valve, 2007) also uses stylized shading, but opts for a more customized look based on early 20th century commercial illustration, in addition to heavily exaggerated characters and carefully crafted color palettes [32].

  10. 10.

    Of course, the maxim “garbage-in →garbage-out” still applies. In general, most NPR algorithms work better with higher contrast images than with lower contrast images. As such, a tone-mapping or normalization pre-processing stage can be used to improve the input to many NPR algorithms. Similarly, bilateral filtering or similar edge-preserving smoothing operations may be used to reduce sensor and other noise before further NPR processing is applied (see also Chap. 5).

  11. 11.

    Some may find this statement objectionable. For alternative views, the interested reader may search the web for “Computational Creativity”.

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  1. Adobe Systems, Inc., Seattle, USA

    Holger Winnemöller

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  1. Holger Winnemöller
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Correspondence to Holger Winnemöller .

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  1. School of Computer Science & Informatics, Cardiff University, The Parade, Roath 5, Cardiff, CF24 3AA, United Kingdom

    Paul Rosin

  2. Centre for Vision Speech & Signal Proc., University of Surrey, Guildford, GU2 7XH, Surrey, United Kingdom

    John Collomosse

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Winnemöller, H. (2013). NPR in the Wild. In: Rosin, P., Collomosse, J. (eds) Image and Video-Based Artistic Stylisation. Computational Imaging and Vision, vol 42. Springer, London. https://doi.org/10.1007/978-1-4471-4519-6_17

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