Video Codec for Classical Cartoon Animations with Hardware Accelerated Playback

Sýkora, Daniel; Buriánek, Jan; Žára, Jiřı́

doi:10.1007/11595755_6

Cited by 8 publications

(7 citation statements)

References 22 publications

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“…We now compare our results with those from the methods in [1], [2], [3], [4], [5], using images taken from their work (see Fig. 11).…”

Section: Comparisonmentioning

confidence: 93%

“…S ykora et al's [3], [4], [5] work on vectorization of cartoon animations is the most closely related previous work to ours. In their approach, cartoons must have a foreground layer consisting of dynamic regions each enclosed by clearly visible outlines.…”

Section: Related Workmentioning

confidence: 95%

“…While S ykora et al's method [3], [4], [5] also detects decorative lines forming outlines of regions, they rely on an artistic style which produces closed decorative lines. Unfortunately, decorative lines do not take this form in most recent cartoon art styles: often, at least some regions are only delimited by edges (i.e., color steps) in the image rather than explicit decorative lines.…”

Section: Decorative Line Detectionmentioning

confidence: 99%

“…11). S ykora et al's method [3], [4], [5] imposes very strong constraints on the cartoons processed, i.e. regions must have thick, closed black outlines and constant color.…”

Section: Comparisonmentioning

confidence: 99%

“…Furthermore, none of them considers temporal coherence. S ykora et al [3], [4], [5] made significant advances in vectorizing cartoons, but their approach rely on a particular drawing style in which meaningful regions are enclosed by thick bounding lines, which is not appropriate to many modern cartoon styles.…”

Section: Introductionmentioning

confidence: 99%

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Vectorizing Cartoon Animations

Zhang

Chen

Zhang

et al. 2009

IEEE Trans. Visual. Comput. Graphics

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Abstract-We present a system for vectorizing 2D raster format cartoon animations. The output animations are visually flicker free, smaller in file size, and easy to edit. We identify decorative lines separately from colored regions. We use an accurate and semantically meaningful image decomposition algorithm, supporting an arbitrary color model for each region. To ensure temporal coherence in the output, we reconstruct a universal background for all frames and separately extract foreground regions. Simple user-assistance is required to complete the background. Each region and decorative line is vectorized and stored together with their motions from frame to frame. The contributions of this paper are: 1) the new trapped-ball segmentation method, which is fast, supports nonuniformly colored regions, and allows robust region segmentation even in the presence of imperfectly linked region edges, 2) the separate handling of decorative lines as special objects during image decomposition, avoiding results containing multiple short, thin oversegmented regions, and 3) extraction of a single patch-based background for all frames, which provides a basis for consistent, flicker-free animations.

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“…We now compare our results with those from the methods in [1], [2], [3], [4], [5], using images taken from their work (see Fig. 11).…”

Section: Comparisonmentioning

confidence: 93%

Section: Related Workmentioning

confidence: 95%

Section: Decorative Line Detectionmentioning

confidence: 99%

“…11). S ykora et al's method [3], [4], [5] imposes very strong constraints on the cartoons processed, i.e. regions must have thick, closed black outlines and constant color.…”

Section: Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Vectorizing Cartoon Animations

Zhang

Chen

Zhang

et al. 2009

IEEE Trans. Visual. Comput. Graphics

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Learning to Synthesize Graphics Programs for Geometric Artworks

Bing,

Zhang,

Cai

2024

Lecture Notes in Computer Science

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Region-based structure line detection for cartoons

et al. 2015

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Cartoons are a worldwide popular visual entertainment medium with a long history. Nowadays, with the boom of electronic devices, there is an increasing need to digitize old classic cartoons as a basis for further editing, including deformation, colorization, etc. To perform such editing, it is essential to extract the structure lines within cartoon images. Traditional edge detection methods are mainly based on gradients. These methods perform poorly in the face of compression artifacts and spatially-varying line colors, which cause gradient values to become unreliable. This paper presents the first approach to extract structure lines in cartoons based on regions. Our method starts by segmenting an image into regions, and then classifies them as edge regions and non-edge regions. Our second main contribution comprises three measures to estimate the likelihood of a region being a non-edge region. These measure darkness, local contrast, and shape. Since the likelihoods become unreliable as regions become smaller, we further classify regions using both likelihoods and the relationships to neighboring regions via a graph-cut formulation. Our method has been evaluated on a wide variety of cartoon images, and convincing results are obtained in all cases.

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Video Codec for Classical Cartoon Animations with Hardware Accelerated Playback

Cited by 8 publications

References 22 publications

Vectorizing Cartoon Animations

Vectorizing Cartoon Animations

Learning to Synthesize Graphics Programs for Geometric Artworks

Region-based structure line detection for cartoons

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