The Visual Computer manuscript No.
(will be inserted by the editor)

Bing-Yu Chen · Yutaka Ono · Tomoyuki Nishita

Character Animation Creation using Hand-drawn Sketches

Abstract To create a character animation, a 3D character model is often needed. However, since the humanlike character is not a rigid-body, to deform the character model to fit each animation frame is a tediouswork. Therefore, we propose an easy-to-use method for
creating a set of consistent 3D character models fromsome hand-drawn sketches while keeping the projectedsilhouettes and features of the created models consistent
with the input sketches. Since the character models possess vertex-wise correspondences, they can be used forframe-consistent texture mapping or for making character animations. In our system, the user only needs toannotates the correspondence of the features among the
input vector-based sketches; the rest processes are all
performed automatically.
Keywords Cel Animation · Non-Photorealistic Rendering · 3D Morphing · Consistent Mesh Parameterization ·Sketches

1 Introduction
The techniques of computer graphics are widely used forsupporting the creation process of animations. In the traditional approach, animators had to draw each frame ofan animation by hand on paper or cel. This has now beensuperseded by a method in which the frames are drawn
using computer-assisted tools, or by rendering the scenes
using 3D models. Moreover, if the animators use vectorbased drawings rather than raster-based paintings, they
Bing-Yu Chen
National Taiwan University
E-mail: robin@ntu.edu.tw
Yutaka Ono
The University of Tokyo
E-mail: ono@nis-lab.is.s.u-tokyo.ac.jp
Tomoyuki Nishita
The University of Tokyo
E-mail: nis@is.s.u-tokyo.ac.jp

can scale the drawings to any size and the images thus require less storage space. Meanwhile, by using 3D models,the animators can add many attractive effects to theiranimations, e.g., shading, shadowing or texture mapping,which are difficult or time-consuming to draw by hand.
However, it is still difficult to construct human-likecharacter models to support the animation making process,since their shapes are often drawn with considerable distortions due to the characters’ motion, changing viewpoints or animators’ exaggerations. Although it might bepossible to make several 3D models whose shapes changewith such distortions, deforming the models manually foreach frame is a very time-consuming task. Therefore, we
propose a method for creating a set of 3D polygon models
that correspond to the input frames of some hand-drawn
sketches. Animators can use the set of models for easily
adding 3D effects, especially for adding shading effects
or shadows to the animation and for mapping textures toa character, while preserving the user-specified featureswith frame-to-frame coherence.
Our method takes a single cut of an animation from asequence of vector-based images drawn by animators as
the input, where each of the images contains the shapeand features of a character in a certain (key) frame of
the animation. The correspondences of the features between the frames are specified by the user. Our systemthen creates a consistent 2D base domain according to
the features and the silhouettes of the character on eachframe. By subdividing the base domain recursively, thesystem generates a set of consistent 2D triangle meshes
that approximate the features and the silhouettes of thecharacter on each frame. After an inflation process, a setof consistent 3D polygon models is created, so that the
projected silhouettes and features of the models are consistent with the input frames. In the all processes, only
the feature specification is operated by the user, the rests
are automatically done by our system.
The created 3D models have the following properties:(1) Silhouette preservation: the projected silhouetteof each created model coincides with that of the character on the corresponding original frame. (2) Frame-

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to-frame correspondences: the created models exhibit vertex-wise correspondences. (3) Feature preservation: all of the features of the input image are embedded in the corresponding model and the projectionof these features coincides on the original frame.
The silhouette preservation property allows the animators to use the set of consistent models that havebeen created for adding shading effects or shadows, andthe frame-to-frame correspondence property allows themto use frame-consistent texture mapping. Texture mapping with user-specified constraints along the input vectors between the input image and the model, as well
as of models, is possible due to the feature preservation property. Moreover, since the created models possess vertex-wise correspondences, the method can assist
the animators to generate in-between shapes among the
input frames by applying morphing techniques.

2 Related WorkTo add attractive and impressive 3D effects onto cel animations, the animators usually require 3D geometric information. The method of obtaining 3D information for
rigid objects is quite straightforward, since they can simply call on modelers to construct 3D models. Those 3Dmodels can be directly rendered by using so-called toonor comic shaders [22], together with several stylized rendering methods [7] [8] [15]. However, for human-like characters, there seems to be no simple solution to obtaining
3D information due to their artistic distortions.
Rademacher [18] presented a typical method to createan animation using a 3D character model, generated bya professional animator. In this method, the animatorgenerated 3D character model is deformed to match several reference images, and the deformed models are theninterpolated to create a 3D geometry whose shape deforms with the changes of viewpoint. Martı́n et al. [13]also presented a related method. Since the animators
manually define the 3D models at each key viewpoint,these methods were able to satisfy the three properties
that are highlighted in our method, i.e., silhouette preservation, feature preservation, and frame-to-frame correspondences, and they could be used for many applications. However, manually editing the 3D models is still atime-consuming task. Li et al. [12] also provide a sketchbased method to generate character animation.
A texture mapping method for cel animation presented by Corrêa et al. [3] also uses 3D models created by animators. Although a reference model must be
created manually, a simple interface for deforming themodel to meet the silhouette preservation and frame-toframe correspondence criteria are provided. Therefore,
this technique may also be used for adding shading effects or shadows. However, since the feature preservation
requirement is only an approximation, it cannot be used

Bing-Yu Chen et al.

for complex textures that must critically satisfy the userspecified constraints.
In order to create a 3D model, Igarashi et al. [6]and Karpenko et al. [10] proposed easy-to-use sketching systems with which the user draws only the silhouette. The systems can then create a 3D model that satisfies the silhouette preservation requirement for a single frame. However, it is not simple to extend this toanimation, since the frame-to-frame correspondence criterion is obviously not considered. A method proposedby Petrović et al. [17] for adding shadows cast by thecharacters on the scenes requires only a small effort on
the part of the animators, because it creates 3D models semi-automatically using the above methods. However, these models do not possess feature preservation orframe-to-frame correspondence properties, so the range
of applications where these models can be used is very
limited.
Some computer vision techniques could be used toconstruct 3D models from 2D tracking-points. However,most of these techniques assume that the object is rigid,
and hence they are not applicable to the characters incharacter animations. Several methods, e.g., those presented by Bregler et al. [2] and by Torresani et al. [21]have been proposed for generating 3D non-rigid models,
but they all require a large number of images and tracking points. Therefore, these methods cannot be applied
for key-frame character animations in general. Our previous work [16] also used some computer vision methods
to construct a set of consistent 3D character models froman existing cel animation for adding some effects into theoriginal animation. Hence, the methods presented in thispaper are different from the previous one, since the information on some hand-drawn sketches is not so muchas that on a cel animation which has more frames than
the input sketches.
In this paper we aim to identify a method that canbe used to create consistent 3D models featuring silhouette preservation, feature preservation and frame-toframe correspondence properties. Applications for thesemodels include adding shading effects and shadows andmapping textures within the animators’ constraints. The
burden for the animators with this technique is not so
different from the method provided by Petrović et al.
[17].

3 System Overview
In this section, the system overview is described from ananimator’s viewpoint. Initially, he or she loads a sequenceof images, which are hand-drawn sketches, representing
some key frames of a character animation shown in Fig. 1(a)∼(c). The animator then overwrites some stroke vectors on the features of the images as shown in Fig. 1(d)∼(f). This work can be done by using some commercial tools which can convert raster-based or scanned

Character Animation Creation using Hand-drawn Sketches

hand-drawn sketches into vector-based images. Of course,
if the original input images are already vector-based likethe example shown in Fig. 5 (a), this step can be omitted. After specifying the corresponding points and paths
between the frames by adding some ID numbers, the preprocessing setup step has been completed. The animator
can then obtain a set of consistent 3D models automatically, as shown in Fig. 1 (g)∼(i). These models can thenbe used for further applications, such as texture mappingand shadowing, as shown in Fig. 1 (j)∼(l).

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4 Generation of Consistent 2D Meshes
After the pre-processing setup described in Section 3,
we now have F vector-based images as Fig. 1 (d)∼(f),where F is the number of input frames. These images
are treated as F sets of 2D (x-y) planar graphs, and eachgraph is denoted as Gf = (Wf , Pf ), f = [1, F ], where Wf
is a set of points in <2 and Pf is a set of finite simple
paths in <2 connecting two different points in Wf , andeach path is sampled to a polyline. Moreover, we assume
that the graphs are consistent which can be guaranteedby guiding the user’s input, where two graphs are consistent means that there are one-to-one correspondencesamong their points and paths as the two graphs shownin Fig. 2 (a).
To generate 2D meshes from the graphs, it is necessary to convert the graphs so that they contain no isolated points and paths as shown in Fig. 2 (b). Therefore,
we separate our consistent 2D triangle mesh generation
algorithm from a sequence of input graphs into two steps.
In the first step (Section 4.1), we create a set of consistentbase domains, which are consistent triangulated graphs
G0f (Gf ) = (Wf , Pf0 ) of Gf = (Wf , Pf ), where Pf0 ⊆ Pf ,as shown in Fig. 2 (c) for all of the frames, which means
some paths are inserted into the graph Gf to make eachpatch has only three points and paths, and a patch isdefined as a closed region bounded by the paths of thegraph.
In the second step (Section 4.2), we create a set of
consistent 2D triangle meshes Mf in which the triangulated graphs G0f are embedded by subdividing each patchof G0f , as shown in Fig. 2 (c).
4.1 Consistent Graph Triangulation

(j)

(k)

(l)

Fig. 1 User input hand-drawn sketches of a dancing bearand corresponding output models. (a)∼(c) Three of the six
input sketches. (d)∼(f) Converted stroke vectors from input
sketches with user-specified correspondences. (g)∼(i) Output
3D models shown in wireframe. (j)∼(l) Texture-mapped models with shadows using toon rendering.

With some complex characters, some areas of thecharacter are hidden by others, for example, the forearms
and the upper arms of the dancing bear shown in Fig. 1.
In this case, the animator has to draw some stroke vectors and specify the correspondence of the missing partsby separating the input images into multiple layers. This
decomposition is natural for the process of making celanimations [4].

The algorithm described in this section creates a set of
consistent base domains, which are triangulated graphs
G0f (Gf ) = (Wf , Pf0 ) from a set of consistent input graphs
Gf = (Wf , Pf ), by adding the paths, one by one, to
Gf . This method, which sequentially adds paths to thegraph, is modified from the method described by Kraevoy et al.
[11]. In order to describe the algorithm clearly, we use
G∗f = (Wf , Pf∗ ) as an intermediate graph between thegiven set of consistent graphs Gf = (Wf , Pf ) and theoutput set of consistent base domains G0f (Gf ) = (Wf , Pf0 )for all of the frames. We first compute a path q1 connecting {p1,i , p1,j }, where i 6= j and p1,i , p1,j ∈ W1 ,which does not cross the unbounded region and which
minimizes the path length. If path q1 is found, thenwe sequentially compute paths q2 , ..., qF for connecting{p2,i , p2,j }, ..., {pF,i , pF,j }, respectively, where q2 , ..., qF
are corresponding paths with q1 , so that the graphs G∗1 =(W1 , P1∗ ∪ {q1 }), ..., G∗F = (WF , PF∗ ∪ {qF }) are still consistent.
In order to find paths q2 , ..., qF , we need to search all
possible paths in the graphs from the standpoint of the

4Bing-Yu Chen et al.

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Fig. 3 Path search/computation using a trapezoidal map.
(a) An input graph. (b) A trapezoidal map of (a) with its”road map”. (c) Four topologically different paths for connecting yellow points. (d) Optimized path derived from thered path in (c).

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Fig. 2 (a) Input graphs of two frames. Green numbers show
the corresponding ID numbers for points and blue numbers
are for paths. (b) Triangulated graphs of (a). (c) Output consistent 2D triangle meshes.

topology. To achieve this topological search and to compute the paths, we use trapezoidal maps of the graphs asshown in Fig. 3. The paths are generated by connecting
the centroids of the trapezoids and the centers of the vertical extensions, as in Fig. 3 (b) and (c). The paths arethen optimized by removal of the redundant points. The
conditions for removing the redundant points are that(1) removing the point does not change the topology ofthe path, and (2) removing the point does not move aremaining path too close to other points or paths. The
second condition is necessary to avoid degeneracy in thefollowing algorithms. For example, removing the squared
point in Fig. 3 (d) is topologically possible, but it would
make the path too close to other points or paths. Afterall possible paths are found, we will choose the path withthe same topology as the path in the first frame. Once thepaths q1 , ..., qF are decided and added to G∗1 , ..., G∗F , wewill check if G∗1 , ..., G∗F have become triangulated graphto stop or continue the triangulation process.
Note that this triangulation algorithm is not symmetric, because graph G∗1 is dealt with first, and the others
follow on. Although it is possible to make the algorithm
symmetric by further computing path sets for G∗2 , ..., G∗F
as the first steps and then deciding the minimum average

4.2 Consistent Face Subdivision
We now have consistent base domains G0f (Gf ) = (Wf , Pf0 ),and each patch in a base domain has a simple boundary
defined by three paths as shown in Fig. 2 (b). To create consistent 2D triangle meshes Mf , in which the input graphs Gf are embedded as shown in Fig. 2 (c), we
first define 2D meshes, Mf∗ = (Wf , Kf∗ ), by identifying
G0f as meshes, where Kf∗ is a simplicial complex derived
from the paths of G0f . Since the paths of G0f are represented by polylines, Mf∗ may not consist of triangles
or be consistent among frames in general. To establish
consistency over Mf∗ , we apply an edge-split operator to
Mf∗ to make the boundary of each face have the same
number of vertices among frames as shown in Fig. 4 (b).
A consistent triangulation method for simple boundary
polygons may then be applied to all the faces of the Mf∗
independently, the results of which are shown in Fig. 4(c), and we use Mf0 to denote the generated consistent
2D triangle meshes. The triangulation method we usedhere is an adaptive semi-regular refinement method (acombination of 4-to-1 and 2-to-1 subdivisions).
Although Mf0 are consistent 2D triangle meshes, they
may have some undesirable creases, due to the paths thatwere added for graph triangulation, and thus may not bevalid. Therefore, we apply a smoothing method to Mf0
based on the algorithm of Freitag et al. [5] that moves
each vertex locally to minimize an energy function, whileconstraining the positions of the vertices corresponding
to Gf and get Mf .

Character Animation Creation using Hand-drawn Sketches

G1

(a)

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5

for two different layers, the paths are regarded as stitches.
Two meshes are combined by uniting the vertices of thestitches. After combining the layers, they are smoothly
shifted and sheared so that they do not intersect witheach other.
Since the animators draw the characters aesthetically,
it is difficult to generate their 3D shapes fully automatically. In addition to the above automatic inflation
method, we also provide several tools to let the animators
manually adjust the z-coordinate of the vertices if necessary, such as the methods described in [17] [18] [19].
We only allow the changes in the positions of vertices
along the direction of the projections in order to maintain the silhouette preservation and the feature preservation properties.

5 Results and Applications(b)(c)
Fig. 4 A process of consistent face subdivision. (a) The
input patches of two base domains G 01 (G 1 ) = (W 1 , P 01 )and G 02 (G 2 ) = (W 2 , P 02 ). The yellow points are the corresponding points in W 1 and W 2 . (b) The results after applying edge-split operators to (a). (c) Consistent 2D triangle
meshes are generated by subdividing (b).

4.3 Consistent 3D Meshes Generation
After creating consistent 2D (x-y) triangle meshes M1 , ...,MF , we inflate each vertex of the meshes to determine
its z(depth)-coordinate. We apply an inflation method
to the boundary vertices of Mf , based on the method
proposed by Igarashi et al. [6], and create a height field
for the positions inside the boundary. Each z-coordinateof the vertices of Mf is determined from the height field.
Since the values of the height field for frame f are only
dependent on the boundary of Mf , frame-to-frame coherence with respect to the z-coordinates is not considered.
To maintain the frame-to-frame coherence, we apply an
optimization method based on Taubin’s paper [20], tosmooth the depth of the vertices, both inter-frames andwithin-frame, by an iterative process.
If the characters in the input frames are composedof several layers, we create the 3D meshes separately foreach layer and then bring them together as a composition. If the user has defined the same closed input paths

The dancing bear models shown in Fig. 1 (j)∼(l) arecreated from six input images. Three of these are shownin Fig. 1 (a)∼(c). In the pre-process step, 60 curves are
drawn on each frame. By using the current system, it
takes about 20 seconds to produce six consistent 3Dmodels using a desktop PC with an Intel Pentium 4
1.7GHz CPU. Each model contains 6,018 faces (triangles) and 3,280 vertices. To overwrite stroke vectors on
the input hand-drawn sketches and specify the correspondences of 59 features among the six frames takes 30
minutes through our user interface, which is similar to
the time taken by other tools for object space morphing.
The running dinosaur models shown in Fig. 5 (b)are also created from six input images. Three of theseare shown in Fig. 5 (a). It takes about 40 seconds to
produce six consistent 3D models with 86 features, eachof which contains 4,862 faces and 2,550 vertices. Since theconstructed dinosaur models are three-dimensional, we
can change the viewpoint to render the dinosaur modelas the images shown in Fig. 5 (c). However, since we havethe input images from only one viewpoint, changing the
viewpoint too large will cause some errors due to the lackof the information from other viewpoints.
The created set of 3D character models can be used
for the following applications.
Shading Effects and Shadows: Fig. 6 shows two
synthesized scenes that use different illumination conditions. In Fig. 6 (a), we use low contrast diffusion colors tosimulate an evening scene. On the other hand, in Fig. 6(b), we use high contrast diffusion colors and apply specular effects to mimic the light through trees. The lighting
conditions and the position of the ground can be changedby the user. To add shading effects to the characters,
we implemented our rendering algorithm on programmable graphics hardware (NVIDIA GeForce FX), andwere able to render the scenes in real-time. Scenes that
include shading effects or shadows can be easily generated once the 3D models have been created. It typically6Bing-Yu Chen et al.

(a)Fig. 7 Simple textured models. Note that the texture on
the groins of both of the dinosaur models is continuous.
(b)(c)
Fig. 5 An example of a running dinosaur. (a) Three of thesix input vector-based images. (b) Texture mapped models
using toon rendering. (c) Viewed from another viewpoint.

takes two or three minutes to change the illumination
conditions and the directions of the light sources. Since
our method can be seen as an extension of the work byPetrović et al. [17], adding shadows or shading produces
almost the same results as their method.

specified stroke vectors. The model shown in Fig. 8 (a) is
the same as that shown in Fig. 8 (b) which is a close-up
view of Fig. 1 (k), but the eyes and the mouth of the bearmodel in Fig. 8 (a) have some errors. This unpleasant effect is caused by the differences in the vertex densities ofthe models in the regions of the stroke vectors, as in themodels shown in Fig. 1 (g) and (h). Although we can put
hard constraints onto the stroke vectors, we cannot ensure the uniformity of the vertex densities around them.
This problem is closely related to the manner of drawing silhouettes in an artistic style [7] [8] [15]. Since in acharacter animation the features are the most importantparts, the problem must be solved.

(a)
(a)

(b)

Fig. 6 (a) Long shadows cast by two bears. A shadow causedby one bear is cast onto another bear. The background image
is taken from Corrêa et al.’s paper [3]. (b) Simulating theeffect of light through the trees.

Texture Mapping: Since the 3D models that werecreated exhibit feature-preservation and frame-to-frame
correspondence properties, mapping a texture image onto
each model or obtaining intermediate models is straightforward. The stroke vectors drawn on the images by the
animator work as guides or constraints for texture mapping or morphing. Fig. 7 shows a simple example of mapping one texture image onto two models. Note that thepattern of the texture corresponds on each model. We
transfer the same texture from the first model to others by giving the same texture coordinates to the corresponding vertices, i.e., texture transfer.
However, simple texture mapping is not sufficient insome cases. Fig. 8 (a) shows a bad example, since it
produced some serpentine lines around the animator-(b)

Fig. 8 (a) A texture-mapped model with some errors. Notethat the eyes and the mouth are drawn with serpentine lines,
which are quite different from (b). (b) A correct texturemapped result which is a close-up view of Fig. 1 (k).

In our approach, we record the texture around eachanimator-specified stroke vector separately from the ordinal textures by parameterizing its width onto a vertex sequence that corresponds to the stroke vector. To
render the vertex sequence corresponding to the stroke
vectors, we first check whether (a part of) the vertex sequence is visible. If it is, we disable the z-buffer, generate
triangle strips in the image space according to the parameterized width and draw them directly onto the image
plane. Fig. 8 (b) (also Fig. 1 (k)) shows the modified
texture-mapped model of Fig. 8 (a).
The texture-mapped dinosaur model shown in Fig. 7
is composed of several layers, e.g., the body and the left
leg are two different but connected layers. By applying
the same constraints to the stitches of the connected
layers, the texture on connected layers can be mapped7smoothly. Note that the texture on the groin of the dinosaur model shown in Fig. 7 is continuous.
Morphing and Shape Blending: To morph models by using their vertex-wise correspondences, many 2D
or 3D morphing methods [1] [9] [14] might be applied.
However, most of existing morphing methods are designed for morphing between two models, and cannot beeasily extended to more than two models. Hence, we currently chose to use a simple Spline interpolation method
to construct the intermediate models, as shown in theupper row of Fig. 9, for generating a smooth animation sequence. Moreover, by specifying the corresponding strokes and features onto the images of two different
characters, two 3D models with a consistent mesh parameterization can be constructed. Then, the morphing
sequence between the two character models can also be
generated. To blend two or more different character models can also be achieved.

the bear, we can still not generate a set of pseudo-viewdependent models from the front of the bear to the back.

space

Character Animation Creation using Hand-drawn Sketches

timeFig. 9 The upper row shows the intermediate models constructed between the models shown in Fig. 1 (j) and (k). The
middle row shows the pseudo-view-dependent models generated from the models in the upper and lower rows. The lower
row shows the morphing sequence generated from other two
input frames from another viewpoint.

Pseudo-view-dependent Models: Given sets of
input frames from different viewpoints, by specifying thecorresponding strokes and features onto the images, the3D models that interpolate the viewpoints can be constructed as shown in the middle row of Fig. 9.We thus
can help the animators to generate both temporal andspatial intermediate shapes. Since the models are constructed from a set of consistent 2D graphs, if there areno corresponding features on the input frames, we can
not construct the models. Therefore, even if the user
gives an input of a set of images to show the back of

6 Conclusions and Future WorkIn this paper, we proposed a method for creating a setof consistent 3D models from a sequence of hand-drawn
strokes. The models have the following properties. (1)Their projected silhouettes coincide with the input strokes,
and therefore they can add plausible shading effects or
shadows to a scene. (2) They possess vertex-wise correspondence, so it is possible to obtain a continuous animation sequence by interpolating their coordinates or to
add the same textures to all of the models by propagating the texture coordinates to the corresponding vertices.
(3) The correspondence of the vertices can be controlled
by the animators’ drawing strokes, and thus the technique can be applied to morphing or texture mappingwith constraints set by the animators.
The additional effort required of the animators, beyond the traditional process of making cel animations, isonly to specify several correspondences on input strokes,
where the animators would like to place constraints. Thus,
our method can yield a range of applications with only
a minimum of effort. Since our method can construct
several 3D models with a consistent mesh parameterization for different characters, several related applications
might also be achieved.
Since the 3D position of the vertices of the createdmodels are estimated, the surfaces of the created models
may be a little bumpy. This limitation is not so important when we apply toon-shading to the models. Whenit comes to background characters such that used in an
animation of crowds, the details of the character models
are also not so necessary. Therefore, it may be acceptable to use the created models in those cases. Moreover,
our method is also suitable for adding some effects tocel animation like what has been done in [17]. To help
traditional 2D animators to provide a prototype of 3D
character animation is also one of our major contributions. The generated 3D animated character models canthen be further modified by using commercial modelingtools such as Maya.
The following list of topics indicates aspects of thework that we hope to cover in the future: (1) To reduce the labor of animators by finding the correspondences between the input images automatically or semiautomatically. This might become possible by utilizing
computer-vision techniques. (2) To enable the creationof models from non-consistent images. (3) Given a character animation sequence, to transfer the motion of thecharacter to another character which is only drawn on asingle image.
Acknowledgements We thank Dr. Ken-ichi Anjyo (Oriental Light & Magic Inc.) for providing the input images

8(Fig. 1). This work was partially supported by the National
Science Council of Taiwan under the numbers: 93-2213-E002-084.

References
1. Alexa, M., Cohen-Or, D., Levin, D.: As-rigid-as-possible
shape interpolation. In: Proc. SIGGRAPH 2000, pp. 157–
164 (2000)
2. Bregler, C., Hertzmann, A., Biermann, H.: Recovering
non-rigid 3d shape from image streams. In: Proc. CVPR
2000, pp. 2690–2696 (2000)
3. Corrêa, W.T., Jensen, R.J., Thayer, C.E., Finkelstein,
A.: Texture mapping for cel animation. In: Proc. SIGGRAPH 98, pp. 435–446 (1998)
4. Fekete, J.D., Bizouarn, É., Cournarie, É., Galas, T.,
Taillefer, F.: Tictactoon: A paperless system for professional 2-d animation. In: Proc. SIGGRAPH 95, pp. 79–90(1995)
5. Freitag, L.A., Jones, M.T., Plassmann, P.E.: An efficientparallel algorithm for mesh smoothing. In: Proc. IMR
95, pp. 47–58 (1995)
6. Igarashi, T., Matsuoka, S., Tanaka, H.: Teddy: A sketching interface for 3d freeform design. In: Proc. SIGGRAPH 99, pp. 409–416 (1999)
7. Kalnins, R.D., Davidson, P.L., Markosian, L., Finkelstein, A.: Coherent stylized silhouettes. ACM TOG
22(3), 856–861 (2003). (Proc. SIGGRAPH 2003)
8. Kalnins, R.D., Markosian, L., Meier, B.J., Kowalski,
M.A., Lee, J.C., Davidson, P.L., Webb, M., Hughes, J.F.,
Finkelstein, A.: Wysiwyg npr: Drawing strokes directly
on 3d models. ACM TOG 21(3), 755–762 (2002). (Proc.
SIGGRAPH 2002)
9. Kanai, T., Suzuki, H., Kimura, F.: Metamorphosis of arbitrary triangular meshes. IEEE CG&A 20(2), 62–75(2000)
10. Karpenko, O., Hughes, J.F., Raskar, R.: Free-form
sketching with variational implicit surfaces. Computer
Graphics Forum 21(3), 585–594 (2002). (Proc. Eurographics 2002)
11. Kraevoy, V., Sheffer, A., Gotsman, C.: Matchmaker: Constructing constrained texture maps. ACM TOG 22(3),326–333 (2003). (Proc. SIGGRAPH 2003)
12. Li, Y., Gleicher, M., Xu, Y.Q., Shum, H.Y.: Stylizing
motion with drawings. In: Proc. SCA 2003, pp. 309–319(2003)
13. Martı́n, D., Garcı́a, S., Torres, J.C.: Observer dependent
deformations in illustration. In: Proc. NPAR 2000, pp.
75–82 (2000)
14. Michikawa, T., Kanai, T., Fujita, M., Chiyokura, H.:
Multiresolution interpolation meshes. In: Proc. PG 2001,
pp. 60–69 (2001)
15. Northrup, J.D., Markosian, L.: Artistic silhouettes: A hybrid approach. In: Proc. NPAR 2000, pp. 31–38 (2000)
16. Ono, Y., Chen, B.Y., Nishita, T.: 3d character model
creation from cel animation. In: Proc. CyberWorlds 2004,
pp. 210–215 (2004)
17. Petrović, L., Fujito, B., Williams, L., Finkelstein, A.:
Shadows for cel animation. In: Proc. SIGGRAPH 2000,
pp. 511–516 (2000)
18. Rademacher, P.: View-dependent geometry. In: Proc.
SIGGRAPH 99, pp. 439–446 (1999)
19. Singh, K., Fiume, E.L.: Wires: A geometric deformation
technique. In: Proc. SIGGRAPH 98, pp. 405–414 (1998)
20. Taubin, G.: Curve and surface smoothing without shrinkage. In: Proc. ICCV 95, pp. 852–857 (1995)
21. Torresani, L., Hertzmann, A., Bregler, C.: Learning nonrigid 3d shape from 2d motion. In: Proc. NIPS 2003, pp.
577–580 (2003)

Bing-Yu Chen et al.

22. Winnemöller, H., Bangay, S.: Geometric approximations
towards free specular comic shading. Computer Graphics
Forum 21(3), 309–316 (2002). (Proc. Eurographics 2002)

Bing-Yu Chen received the
B.S. and M.S. degrees in Computer Science and Information
Engineering from the National
Taiwan University, Taipei, in
1995 and 1997, respectively,
and received the Ph.D. degree
in Information Science fromthe University of Tokyo, Japan,
in 2003. He is currently an assistant professor in the Department of Information Management and the Graduate Institute of Networking and Multimedia of the National Taiwan
University since 2003. His research interest are mainly for
Computer Graphics, Geometric Modeling, Web and Mobile
Graphics. He is a member of IICM, ACM, and IEEE.

Yutaka Ono received the B.S.
and M.S. degrees in Information Science and Computer Science from the University ofTokyo, Japan, in 2002 and2004, respectively. He is currently working for SEGA Corp.
since 2004. His research interest is mainly for Computer
Graphics, Geometric Modeling, and Computer Animation.

Tomoyuki Nishita received
the B.S., M.S., and Ph.D. degrees in Electrical Engineering from the Hiroshima University, Japan, in 1971, 1973, and1985, respectively. He worked
for Mazda Motor Corp. from1973 to 1979. He has been alecturer at the Fukuyama University since 1979, then became
an associate professor in 1984,
and later became a professor in
1990. He moved to the Department of Information Science of
the University of Tokyo as aprofessor in 1998 and now is
a professor at the Departmentof Complexity Science and Engineering of the University ofTokyo since 1999. He received Research Award on Computer
Graphics from IPSJ in 1987, and also received Steven A.
Coons awards from ACM SIGGRAPH in 2005. His researchinterest is mainly for Computer Graphics. He is a member of
IEICE, IPSJ, ACM, and IEEE.