State of the "Art”: A Taxonomy of Artistic Stylization Techniques for Images and Video

Kyprianidis, Jan Eric; Collomosse, John; Wang, Tinghuai; Isenberg, Tobias

doi:10.1109/tvcg.2012.160

Cited by 244 publications

(152 citation statements)

References 147 publications

(282 reference statements)

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“…For instance, effects created by raster-based filters (e.g., [Winnemöller et al 2006]) cannot be easily represented as strokes. Additionally, we are not aware of any example-based video stylization methods that support keyframes (see Kyprianidis et al [2013] for a survey).…”

Section: Temporally Coherent Nprmentioning

confidence: 99%

Stylizing animation by example

Bénard

Cole²,

Kass³

et al. 2013

ACM Trans. Graph.

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Figure 1: Frame 20 (right) to 34 (left) -top row: stylized animation; bottom row: input shaded images. The two extreme frames are keyframes painted by an artist. Our algorithm synthesized the in-between frames. Note the important variations in terms of shape and appearance (texture and color) during this sequence. The accompanying video illustrates the temporal behavior. AbstractSkilled artists, using traditional media or modern computer painting tools, can create a variety of expressive styles that are very appealing in still images, but have been unsuitable for animation. The key difficulty is that existing techniques lack adequate temporal coherence to animate these styles effectively. Here we augment the range of practical animation styles by extending the guided texture synthesis method of Image Analogies [Hertzmann et al. 2001] to create temporally coherent animation sequences. To make the method art directable, we allow artists to paint portions of keyframes that are used as constraints. The in-betweens calculated by our method maintain stylistic continuity and yet change no more than necessary over time.

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Section: Temporally Coherent Nprmentioning

confidence: 99%

Stylizing animation by example

Bénard

Cole²,

Kass³

et al. 2013

ACM Trans. Graph.

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“…In this section, we use this to present effects of image tooning [19] that uses a simple technique of assigning a region its average color. We illustrate this in [ Figure 7] illustrates the use of the multi-scale structure for a stylization in which core regions and non-core regions are treated differently.…”

Section: Hierarchical Morphologymentioning

confidence: 99%

Multi-scale Image Segmentation Using MSER and its Application

Lee¹,

Oh²

2014

The Journal of the Korea Contents Association

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Multi-scale image segmentation is important in many applications such as image stylization and medical diagnosis. This paper proposes a novel segmentation algorithm based on MSER(maximally stable extremal region) which captures multi-scale structure and is stable and efficient. The algorithm collects MSERs and then partitions the image plane by redrawing MSERs in specific order. To denoise and smooth the region boundaries, hierarchical morphological operations are developed. To illustrate effectiveness of the algorithm's multi-scale structure, effects of various types of LOD control are shown for image stylization. The proposed technique achieves this without time-consuming multi-level Gaussian smoothing. The comparisons of segmentation quality and timing efficiency with mean shift-based Edison system are presented.■ keyword :|Image Segmentation|Image Stylization|Morphology|Multi-scale|

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“…Many non-photorealistic and expressive rendering techniques deal with the stylization of 2D images or videos [Kyprianidis et al 2013;Rosin and Collomosse 2013]. While much of this work was initially motivated by the desire to replicate artistic techniques and was only guided by a subjective visual comparison to existing artwork, researchers have begun to empirically evaluate the effects of stylization [Gooch et al 2010;Isenberg 2013;Salesin 2002].…”

Section: Introductionmentioning

confidence: 99%

Reducing affective responses to surgical images through color manipulation and stylization

Besançon

Semmo

Biau

et al. 2018

Proceedings of the Joint Symposium on Computational Aesthetics and Sketch-Based Interfaces and Modeling and Non-Photorealistic

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Original photo of a lasagna dish.Output of HueShift2. Output of FlowAbs [Kyprianidis and Döllner 2008].Figure 1: Two techniques studied in this article, each using a different strategy for making surgery images easier to look at. ABSTRACTWe present the first empirical study on using color manipulation and stylization to make surgery images more palatable. While aversion to such images is natural, it limits many people's ability to satisfy their curiosity, educate themselves, and make informed decisions. We selected a diverse set of image processing techniques, and tested them both on surgeons and lay people. While many artistic methods were found unusable by surgeons, edge-preserving image smoothing gave good results both in terms of preserving information (as judged by surgeons) and reducing repulsiveness (as judged by lay people). Color manipulation turned out to be not as effective. CCS CONCEPTS• Computing methodologies → Non-photorealistic rendering; Image processing; • Human-centered computing → Empirical studies in HCI ; * Lonni Besançon is also with Linköping University, Sweden.Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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State of the "Art”: A Taxonomy of Artistic Stylization Techniques for Images and Video

Cited by 244 publications

References 147 publications

Stylizing animation by example

Stylizing animation by example

Multi-scale Image Segmentation Using MSER and its Application

Reducing affective responses to surgical images through color manipulation and stylization

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