Non-photorealistic rendering

Non-photorealistic rendering (NPR) is an area of

The term non-photorealistic rendering is believed to have been coined by the SIGGRAPH 1990 papers committee, who held a session entitled "Non Photo Realistic Rendering".^[1][2]

The term has received some criticism:

• The term "
  photorealistic rendering") and artists. For artists—who are the target consumers of NPR techniques—it refers to a school of painting that focuses on reproducing the effect of a camera lens, with all the distortion and hyper-reflections^{[definition needed}
  ] that it creates. For graphics researchers, however, it refers to an image that is visually indistinguishable from reality. In fact, graphics researchers lump the kinds of visual distortions that are used by photorealist painters into "non-photorealism".
• Describing something by what it is not is problematic. Equivalent (made-up) comparisons might be "non-elephant biology" or "non-geometric mathematics". NPR researchers have stated that they expect the term will disappear eventually and be replaced by the now more general term "computer graphics", with "photorealistic graphics" being the term used to describe "traditional" computer graphics.^[citation needed]
• Many techniques that are used to create 'non-photorealistic' images are not rendering techniques. They are modelling techniques, or post-processing techniques. While the latter are coming to be known as 'image-based rendering', sketch-based modelling techniques, cannot technically be included under this heading, which is very inconvenient for conference organisers.

The first conference on non-photorealistic animation and rendering^[when?] included a discussion of possible alternative names. Among those suggested were "expressive graphics", "artistic rendering", "non-realistic graphics", "art-based rendering", and "psychographics". All of these terms have been used in various research papers on the topic, but the "non-photorealistic" term seems to have nonetheless taken hold.

The first technical meeting dedicated to NPR was the ACM-sponsored Symposium on Non-Photorealistic Rendering and Animation (NPAR) in 2000. NPAR is traditionally co-located with the Annecy Animated Film Festival,^[3] running on even numbered years. From 2007 onward, NPAR began to also run on odd-numbered years, co-located with ACM SIGGRAPH.^[4]

3D

Three-dimensional NPR is the style that is most commonly seen in video games and movies. The output from this technique is almost always a

NPR techniques for 3D images include cel shading and Gooch shading.

Many methods can be used to draw stylized outlines and strokes from 3D models, including occluding contours and Suggestive contours.^[6]

For enhanced legibility, the most useful

2D

The input to a two dimensional NPR system is typically an image or video. The output is a typically an artistic rendering of that input imagery (for example in a watercolor, painterly or sketched style) although some 2D NPR serves non-artistic purposes e.g. data visualization.

The artistic rendering of images and video (often referred to as image stylization^[7]) traditionally focused upon heuristic algorithms that seek to simulate the placement of brush strokes on a digital canvas.^[8]

Arguably, the earliest example of 2D NPR is Paul Haeberli's 'Paint by Numbers' at SIGGRAPH 1990. This (and similar interactive techniques) provide the user with a canvas that they can "paint" on using the cursor — as the user paints, a stylized version of the image is revealed on the canvas. This is especially useful for people who want to simulate different sizes of brush strokes according to different areas of the image.

Subsequently, basic image processing operations using gradient operators^[9] or statistical moments^[10] were used to automate this process and minimize user interaction in the late nineties (although artistic control remains with the user via setting parameters of the algorithms). This automation enabled practical application of 2D NPR to video, for the first time in the living paintings of the movie What Dreams May Come (1998).

More sophisticated image abstractions techniques were developed in the early 2000s harnessing computer vision operators e.g. image salience,^[11] or segmentation^[12] operators to drive stroke placement. Around this time, machine learning began to influence image stylization algorithms notably image analogy^[13] that could learn to mimic the style of an existing artwork.

The advent of deep learning has re-kindled activity in image stylization, notably with neural style transfer (NST) algorithms that can mimic a wide gamut of artistic styles from single visual examples. These algorithms underpin mobile apps capable of the same e.g. Prisma

In addition to the above stylization methods, a related class of techniques in 2D NPR address the simulation of artistic media. These methods include simulating the

Artistic rendering

Artistic rendering is the application of