Assisting Storyboarders in Expressive 3D Pose Creation with a 2D

Sketch-based Interface

Sophia Mouajjah

1,2

and Cedric Plessiet

INREV, Paris 8 University, Saint-Denis, France

Superprod Studio, Paris, France

Keywords:

Gestural Interface, Storyboarding, Character Posing, Co-creative Process, Storytelling, Layout, Feedback

Loop, Sketch-based Interface.

Abstract:

Storyboarding is an ideation and prototyping process that constitutes one of the keystones in visual and nar-

rative productions, such as ﬁlmmaking and performing arts. During this step, storyboard artists start giving

poses and expressions to their characters. However, in the case of 3D ﬁlm making, the ﬁnal movie will be

transposed from a 2D to a 3D medium, which means that artists do not have an accurate view of the result

of their work. Existing 3D interfaces do not suit the storyboarders’ needs, as their complexity tend to impede

and alter their creative process. This study focus on the development of an intuitive system that allows artists

to pose 3D characters using simple 2D strokes as an interaction method. Our technique combines several

representation modes to let users incrementally develop their poses in a monocular view. We evaluated the

system by posing various characters with different anatomies and levels of details, which showed that it has

the advantage of being ﬂexible and helps in gaining time compared to the classical keyframe method.

1 INTRODUCTION

As a powerful narrative tool, the storyboard depicts

the story’s actions, rhythm and emotions by offer-

ing the ﬁrst visual aspect of the movie. One of the

main tasks entrusted to storyboarders is the character

staging, acting and the creation of expressions. The

majority of existing storyboard tools provide a 2D

sketching interface, as it allows artists to freely and

intuitively experiment aesthetic and narrative options

by creating expressive visuals. However, these tools

thoroughly ignore the 3D nature of the ﬁnal work. As

a consequence, a gap appears between the 2D and 3D

media, which generates inaccuracies during the tran-

sition between these steps. Not being able to see any

3D feedback prevents the director from checking if

the narrative and visual ideas put in the storyboard

panels will effectively work when transposed into a

3D environment.

If sketching tools are intuitive, 3D techniques re-

main complex and laborious, especially for non ex-

pert users. In the case of keyframe animation, the

user must manipulate 3D controllers and several pa-

rameters, which is quite unnatural. These constraints

would burden and slacken traditional artists and neg-

atively interfere with their creative process.

The main goal of this study is to facilitate the tran-

sition between preproduction and production in the

case of character posing. To do so, we developed

a 3D posing method that exclusively relies on 2D

sketch gestures. Users are inserted into a feedback

loop where they can operate with three representation

modes to build a 3D pose. This system offers an in-

tuitive interface that allows artists to quickly pose 3D

characters in a ﬁxed 2D panel, respecting the main

constraints of the storyboarders. We begin this paper

by exploring the representation methods established

by previous research on the subject. Then, we deﬁne

the challenges that are speciﬁc to the ﬁeld of story-

boarding and we describe the implementation of our

method. Finally, we analyze the results and describe

the improvements to be made in our future works.

2 BACKGROUND

2.1 Abstractions

Poses can be depicted by artists using several repre-

sentation methods that we will call abstractions here,

as you can see in ﬁgure 1.

126

Mouajjah, S. and Plessiet, C.

Assisting Storyboarders in Expressive 3D Pose Creation with a 2D Sketch-based Interface.

DOI: 10.5220/0010782000003124

In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 2: HUCAPP, pages

126-133

ISBN: 978-989-758-555-5; ISSN: 2184-4321

Figure 1: Examples of abstractions that can be interpreted

by sketch posing methods.

2.1.1 Stick Figure

The vast majority of the sketch posing interfaces re-

quire stick ﬁgures as input. Some of them add an

automatic size correction feature, like in (Lin et al.,

2012)’s research. In other methods, stick ﬁgures can

be sketched in a totally free-form way, like in (Choi

et al., 2012) and (Mao et al., 2006)’s works. Stick

ﬁgures have the advantages of being close to the real

structure of the 3D skeleton, which makes them easier

to parse and to interpret foreshortening effects. The

main drawbacks when using stick ﬁgures are that they

imply symmetry ambiguities and don’t provide any

volume hint, nor twist information.

2.1.2 Line of Action

(Guay, 2015) uses abstraction concepts inspired by

traditional artists and animators, such as the line of

action, which is a simple unique curve that indicates

the global stream and dynamic of the pose. Other

systems have integrated this concept to posing oper-

ations such as (Mahmudi et al., 2016), (Low, 2014)

and (

Oztireli et al., 2013). The line of action abstrac-

tion is intuitive, expressive and quick to produce as

it doesn’t involve the process of fully sketching the

character. That makes it particularly suited for incre-

mental processes. However, depth, volume and twist

information can be difﬁcult to interpret directly.

2.1.3 Silhouette

Outline or silhouette representations have the beneﬁt

of helping in the deﬁnition of global shapes and de-

termining the area an element should take on screen.

But they tend to be less intuitive to draw for artists

and hard to parse, as they don’t clearly depict the dif-

ferent body elements and produce symmetry ambigu-

ities. This kind of representation is more suited for

procedurally driven parts such as hair, as we can see

in (Seki and Igarashi, 2017)’s study.

2.1.4 Gesture Drawing

(Bessmeltsev et al., 2016) developed an interface that

uses gesture drawings as input, which are intuitive and

suggestive sketches representing a pose in the least

ambiguous way. Gesture drawings are less technical

than stick ﬁgures, more natural than outlines and less

abstract and ambiguous than lines of action. How-

ever, unlike these simple abstractions, they need a

complex calculation step to parse the input sketches,

which make it difﬁcult to use in real time.

2.1.5 Shape Decomposition

Characters can also be constructed by dividing their

parts into several shapes, such as squares or spheres,

like in (Thorne and Burke, 2004)’s system. (Hahn

et al., 2015) also uses decomposed outlines to rep-

resent body parts.

2.2 Data Requirements

Sketch posing methods can rely on existing motion

databases, like in (Jain et al., 2009) or (Lin, 2006)

technique. Other research also exploit comparisons

between drawings from users and rendered poses

from databases, such as (Lv et al., 2015) and (Wei

and Chai, 2011). Sketches can be used as queries to

retrieve poses in a large database, like (Choi et al.,

2012) and (Xiao et al., 2015) research. More recently,

learning algorithms have been developed to recognize

or reconstruct 3D poses from sketches using datasets,

like in (Akman et al., 2020). We can also note tech-

niques that require user annotations to specify joints

positions, such as in (Gouvatsos, 2018) .

3 CHALLENGES

Storyboard drawings hold speciﬁcities that must be

taken into account when building sketch posing sys-

tems, as they are usually rough and simpliﬁed.

Firstly, our tool should minimize the most tedious

and least artistic tasks to let the user focus more on

an aesthetic and narrative works. Therefore, it has to

be fully automated: we do not want to impose any

labeling step to the user.

Storyboard poses tend to be expressive: artists

use exaggerations and emphasis, such as stretch and

squash deformations, to enhance an emotion, which

may create ﬂawed proportions. It should be taken into

account when analyzing sketches.

Our storyboarding system must handle depth am-

biguities, in the most plausible way: given a 2D pro-

jection, several 3D solutions could correspond to the

same 2D representation.

Moreover, we want to integrate the artist into a

retroactive feedback loop with the digital tool. Thus,

Assisting Storyboarders in Expressive 3D Pose Creation with a 2D Sketch-based Interface

127

the algorithms must be fast enough to offer a 3D feed-

back in real time. To let the user reﬁne his work pro-

gressively, the workﬂow has to remain incremental.

In addition, we don’t want to confuse, disturb

or slow down the storyboarder while conceiving the

panels. Sketching should be the unique interaction

mode. No 3D operations should be needed to pose

the character. As a consequence, the system has to

stay monocular: artists should be able to create the

pose exclusively into their frame view.

Finally, we want the tool to be usable by any kind

of animation production team and for any type of

project. As a consequence, the algorithm should not

be based on any pose or motion database, which tends

to be limited to realistic bipedal characters.

4 OVERVIEW

In our sketch posing method, we provide a combina-

tion of sketching tools the storyboarder can employ

according to his needs. The majority of the interac-

tions with the system are done by sketching. During

the session, the artist is always included in a retroac-

tive feedback loop, as all of his actions are imme-

diately applied to the 3D scene and displayed in the

viewport. The user interface is visible in ﬁgure 3-A.

5 IMPLEMENTATION

5.1 Architecture

Our sketch posing tool is divided in two sections, as

you can see in ﬁgure 2. The ﬁrst one is the core sys-

tem: it contains several modules that are necessary for

the pose computation. The abstraction modules deﬁne

useful objects that will be exploited during the pose

estimation stage, such as the camera, the stroke and

the 3D object armature. The posing modules hold the

three posing tools: global posing, line posing and the

sphere manipulator, their algorithms will be described

in 5.3, 5.4 and 5.5. These tools need the user settings

and geometry modules to perform calculations. The

output data of the core system depends on the posing

tool selected, it can be positions or rotations to up-

date in the scene, with a reference to the labels of the

armature elements to edit.

5.2 Scene Data Management

The ﬁrst step in our sketch posing system consists in

gathering all the required data from the storyboard

Figure 2: Sketch posing system architecture and modules.

scene and organize them in order to ease the pose cal-

culation. The plugin part of our system extracts re-

quired data from a digital content creation tool, and

the core part structures it to handle pose estimation.

Our system assumes the 3D camera has already

been placed in the 3D scene. Thus, the framework

takes several camera parameters as input, such as the

normalized world transformation matrix and the di-

rection vector.

The second data type we must handle is the 2D

sketch stroke. A stroke is a curve formed by a set

of ordered points, usually created with a graphic pen

tablet. In our system, strokes are drawn on a 2D plane

that is parallel to the camera clipping planes. We ex-

tract the position of each stroke point in the world

space coordinate system, as well as the pen pressure

values.

Regarding the character skeleton, we made the

choice to take joints positions and bones labels as in-

put rig data to our system. Bones are segments that

connect a ﬁrst joint (head joint) to a terminal joint

(tail joint). They can be rotated by taking the tail joint

as the center of rotation. Joints are the smallest rig

elements and represent the point at which bones are

connected.

5.3 Line Posing

The line posing tool allows artists to set up a character

pose by sketching strokes onto a 3D rigged object. In

our system, the bone length remains constant and the

ﬁrst joint of the chain is never moved. Line posing

operations consist in selecting the right bone chain to

edit, analyze the curve to identify its type and parse

it to extract landmark points. Then, the tool replaces

the joints in 3D space and computes new bone rota-

tions. The plugin picks this data and applies it to the

armature in the 3D viewport. The following sections

describe the process of line posing.

HUCAPP 2022 - 6th International Conference on Human Computer Interaction Theory and Applications

128

5.3.1 Body Part Selection

The ﬁrst step of our line posing process consists in

identifying the body part to edit. For now, we decided

to deﬁne the editable chain according to its proximity

to the user stroke. To do so, we transpose the stroke

points and each chain’s ﬁrst joint to screen coordi-

nates. Then, we select the chain for which its top

joint is the closest to the ﬁrst stroke point. Finally,

the stroke is translated to make its ﬁrst point lie onto

the chain’s ﬁrst joint in the camera view.

5.3.2 Stroke Type Analysis

The tool must be able to handle various stroke styles.

According to his needs, the user can trace stiff an-

gular lines, which can be similar to the kind of lines

we ﬁnd in stick ﬁgures. These curves usually have

several marked turning points, which are clues that

can be used to identify joint positions. The second

type of shape handled by our line posing tool gath-

ers smoother and more supple lines that do not have

marked turning points. They are generally used by

artists to indicate slighter and more subtle intentions

in body pose.

Both types of line are represented in ﬁgure 3-B

and must be parsed differently to make the posing

system more accurate. However, we think the user

shouldn’t have to manually activate parameters in the

interface to indicate the kind of stroke he intends to

draw. As a consequence, we ﬁrst analyze the input

curve to automatically identify the curve type we will

have to process.

To do so, we use the sinuosity index theorized by

(Mueller, ). We compare the result with an arbitrary

threshold value ε as illustrated in the inequation 1.

n−1

∑

i=0

−−−→

i+1

−−→

> 1 −ε (1)

If the ratio is superior to the threshold value, the

stroke will be parsed as an angular stroke. By default,

we set the threshold value as 0.05.

5.3.3 Joint Landmark Detection and

Replacement

Parsing Angular Lines and Replacing Joints. The

system starts by looking for landmarks, which are

points on the 2D stroke that match with the chain

joints. Those points are extracted using a variant

of the Ramer Douglas Peucker algorithm (Douglas

and Peucker, 1973) that takes the number of required

points as input, which corresponds here to the number

of joints.

Once the landmark points have been extracted, we

must inversely project them in the 3D world space and

determine each joint’s new position. For all of the

landmark points, we compute their depth order (see

5.3.4). Then, for each bone in the chain, we build a

sphere with the bone head joint in worldspace coordi-

nates J

as center and the bone length Bl

as radius.

We also build the segment from the camera position

pos

to the tail joint’s matching landmark point on the

stroke L

j+1

. Next, we compute the intersection point

j+1

between the line and the sphere to get the current

bone’s tail joint J

j+1

new position in world space. If

several points have been found, we use the depth mask

computed previously to select the nearest or farthest

point from the camera. A representation of this pro-

cess can be viewed in ﬁgure 3-C for the ﬁrst iteration.

Figure 3: User interface screenshot (A). Line types (B). An-

gular line joint repositioning process and bone angle com-

putation at iteration 0 (C). Bone rotation computation when

parallel to the camera clipping plane (D).

If no intersection point could be found, which

means that the segment between the landmarks is

longer than the bone, we consider that the bone is

parallel to the camera clipping plane. In that case,

the system looks for the projection of the tail joint’s

matching landmark point Lpro j

j+1

from the camera

position on the plane that is normal to the camera di-

rection

−−→

dir

and passing by the current head joint J

Then, we search for the point on the line J

Lpro j

j+1

that is at the Bl

distance from the head joint. The tail

joint position J

j+1

is updated with this new position,

as described in ﬁgure 3-D. To handle cases where the

represented bone segment is too long, two modes are

available: by default, the system sticks to the land-

mark positions. Otherwise, if we want the next joints

in the chain to be adjusted to preserve the global shape

of the stroke, we compute the difference from the

original landmark position L

j+1

to the new tail joint

position J

j+1

in screen space coordinates. Then, we

update the following landmarks in the list L

by sub-

tracting their position with the computed difference,

and we set their new world space position L

accord-

ingly. We continue the iterations until the last joint of

the chain has been replaced.

Assisting Storyboarders in Expressive 3D Pose Creation with a 2D Sketch-based Interface

129

Parsing Smooth Lines and Replacing Joints. The

ﬁrst step, described in ﬁgure 4, consists in ﬁnding the

new position of the last chain joint J

in worldspace

coordinates according to the last stroke point S

. We

compute the intersection point I

between the line

from the camera position C

pos

to the last stroke point

with the sphere that has the ﬁrst chain joint J

as center and the chain total cumulative bone length

Cl as radius. If an intersection point is detected, we

replace the last joint position with it.

Figure 4: Calculation and replacement of the last joint of

the chain if the bone is foreshortened.

Else, we consider that the chain is parallel to the

camera clipping plane. The stroke points are pro-

jected on the plane P

that is normal to the camera

direction and passing by the ﬁrst joint J

. We have

to ﬁnd the intersection point between the bone chain

and the projected stroke Spro j

by maximizing its

length. To do so, for each projected stroke segment

Spro j

i+1

, we compute the intersection point

between the current segment and the circle that has

the ﬁrst joint J

as center and the chain length Cl as

radius, lying on P

. We update the position of the

last joint J

to the ﬁrst intersection point found (ﬁg-

ure 5-A).

Figure 5: Replacement of the last joint of the chain if it is

parallel to the camera clipping plane (A). Replacement of

the bone chain to match the stroke shape at iteration 0 (B).

Then, each intermediate joint J

in the chain is

replaced on the line from the ﬁrst to the last joint

with respect to each original bone length Bl

Lastly, we determine the ﬁnal position of the in-

termediate joints to make them consistent with the in-

put curve (ﬁgure 5-B). For each bone in the chain,

the system computes a projection point J pro j

the bone head joint J

on the plane P

that is nor-

mal to the camera direction and passing by the bone

tail joint J

j+1

. Thereafter, for each stroke segment

, we project its terminals onto P

. We look for

an intersection point between the projected segment

Spro j

i+1

and the circle Circle

constructed

using the projected joint J pro j

as center and the

distance J pro j

j+1

from the projected head joint to

the tail joint as radius. For each potential intersection

point I

, we compute the ratio r

between the dis-

tance Spro j

from the stroke segment’s ﬁrst point

to this point and the distance Spro j

Spro j

i+1

from

the stroke segment’s ﬁrst point to its last point. If sev-

eral intersection points have been found, we take the

point that is associated with the highest ratio r

max

. Fi-

nally, we assign this point position value to the current

tail joint J

j+1

position.

5.3.4 Depth Order

As described in the background section 2, by us-

ing the bone’s real length and the parsed stroke seg-

ment’s length, we can compute the joints’ depth val-

ues. However, if the bone is not normal or parallel

to the camera plane, two solution points are available

for the tail joint: the bone can point towards the cam-

era or in the opposite direction. To resolve this am-

biguity, we decided to establish the depth speciﬁca-

tion in the artist’s workﬂow. As it has already been

done in (Thorne and Burke, 2004)’s work, we took

inspiration from traditional artists who tend to rep-

resent closer elements with thicker lines. Thus, the

user can indicate the proximity of an element to the

camera using pen pressure. In our algorithm, we ﬁrst

extract the pressure value P

for each individual point

on the stroke. Then, for each stroke part between

two landmark points L

and L

j+1

, we compute the lo-

cal pressure mean pmean

of the intermediate stroke

points. Next, we remap the mean rmean

from 0 to

1 using the maximum and minimum global pressure

values pmin

and pmax

, as you can see in the equa-

tion 2. In our system, a pressure threshold α which

defaults to 0.5 is compared with the remapped mean.

If the remapped mean is higher than α, the bone will

be considered pointing forward to the camera. Other-

wise, we will assume it points backwards. The com-

parison values for each bone are stored in a boolean

array to be reused during the joint computation stage.

rmean

= remap(

end

−1

∑

i=i

start

end

− i

start

, pmin

, pmax

, 0, 1)

(2)

5.3.5 Bones Rotations

We use the original and the computed joint position

differences to process each bone rotation. Rotation

values are encoded in quaternions to improve the al-

gorithm efﬁciency, and are sent back to the digital cre-

ation tool to offer visual feedback to the user.

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130

5.4 Sphere Manipulator

The sphere manipulator is constructed of three dif-

ferent strokes: one circle stroke Rs that indicates the

body part to edit and two crossing curved strokes X

and X

that show the rotation direction.

5.4.1 Body Part Selection

To select the right chain to edit, we use the same

method as in 5.3.1, but we use the center of the bound-

ing box of the circle stroke in world space Rs

center

and

the center of the bounding box of each editable bone

chain C h

center

instead.

5.4.2 Rotation Computation

Once the right bone chain has been selected, we must

estimate the required bone rotation according to the

user input sketches. First, we correct the position of

the sphere manipulator by translating the three strokes

to make the circle bounding box center Rs

center

over-

lap the selected chain bounding box center Ch

center

We also compute the intersection point Xi

between

the two cross strokes X

and X

. Then, we calcu-

late the intersection points L

between the line from

the camera position to the cross point C

pos

and

the sphere S with the bone chain bounding box center

center

as center and the chain length Cl as diame-

ter. We do the same operation to ﬁnd the intersection

points M

of the line from the camera to the bone

bounding box center C

pos

center

with the previous

sphere S. For now, we select by default the intersec-

tion point M

that is the closest to the camera. The

desired rotation is represented by the angle between

the vector

−−−−−−−→

center

going from the intersection

point of the chain bounding box center to the chain

bounding box center and the vector

−−−−−−−→

center

that

goes from the intersection point to the chain’s bound-

ing box center. This process is illustrated in ﬁgure 6.

Figure 6: Sphere manipulator description (A). Computation

of the bone chain rotation (B).

Using these two vectors, we are able to build a

quaternion representing the required rotation. This ro-

tation is applied back to the root bone of the chain.

5.5 Global Posing

With the global posing tool, artists can set the object’s

global position by drawing the area it should occupy

on the 2D screen. To do so, we compute the accurate

depth of the 3D character according to the size of the

stroke in screen space and the real character size in

world space.

The algorithm extracts the 3D object and the 2D

stroke bounding boxes. Then, it builds a ﬁrst bound-

ing box vector

−−−→

Ob j

for the 3D object and a sec-

ond one for the stroke

−→

in camera space coordi-

nates. Several modes are available to build the bound-

ing box vectors: height, width and full. For exam-

ple, in height mode, we only take the vector from

the lowest (0,y

min

, 0) to the highest bounding box

point (0, y

max

, 0). In width mode, we construct the

vector with the leftmost (x

min

, 0, 0) and the rightmost

max

, 0, 0) points. By default, we select the vector

from the left bottom shallowest point (x

min

, y

min

, z

min

)

to the right top deepest (x

max

, y

max

, z

max

) point of the

bounding box. Modes can be speciﬁed for each char-

acter in its JSON description ﬁle. According to the

input 3D model, some modes can be more relevant

than others. For example, if the model is particularly

tall and thin, it could be more useful to only take into

consideration the bounding box’s height to compute

the matching depth. On the other hand, if the charac-

ter is signiﬁcantly longer on the x axis, like the whale

in ﬁgure 8, we should use the width mode to make the

computation more accurate.

Figure 7: Computation of the depth of the character in cam-

era space (A). Computation of the ﬁnal position of the char-

acter and its translation vector (B).

We compute the depth of the character in camera

space Char

depth

by using basic projection rules (ﬁgure

7-A). We multiply the norm of the character bounding

box vector

−−−→

Ob j

by the depth of the stroke object in

camera space S

depth

. Then, we divide the result by the

norm of the stroke bounding box vector

−→

Char

depth

−−−→

Ob j

k ∗ S

depth

−→

(3)

The system builds a camera centered landmark

Assisting Storyboarders in Expressive 3D Pose Creation with a 2D Sketch-based Interface

131

Figure 8: Comparaison of our posing method with the classical IK-FK method on pose creation tasks. The table surveys the

time required to create the pose, the number of manipulations required and the number of camera angle changes.

point L

(0, 0,Char

depth

) with the previously com-

puted depth. The point is transposed into world space

coordinates L

. To ﬁnd the ﬁnal position of the 3D

object, we compute the intersection point I

between

the line C

pos

bb center

from the camera position to the

bounding box center of the stroke with the plane par-

allel to the camera clipping plane passing by the trans-

posed landmark point L

. The translation vector

comes from the current bounding box center to the

intersection point

−−−−−−−−−→

Ob j

bb center

. This translation is

applied to the 3D object in the digital content creation

tool (ﬁgure 7-B).

6 RESULTS AND APPLICATIONS

Our system was integrated into Blender and tested us-

ing a pen tablet on 4 characters (ﬁgure 8). We created

the same poses using the classical method with in-

verse and forward kinematic controllers and with our

sketch posing method. The goal was to evaluate the

beneﬁts and the ﬂaws of our technique. We have sur-

veyed the time required to create the pose as well as

the number of manipulations on the character and the

changes of the view angle.

The results showed that our system needs less user

interventions: 12 with our method versus 24 with the

classical method on the third pose. It also requires less

time to create the pose: 6 seconds versus 21 seconds

on a simple pose and 62 seconds versus 296 seconds

on a more complex pose. There were no camera view

changes using our method, as one of the constraints

was to provide a monocular interface.

The work exposed here provides several advances

that make it contribute to the actual state of the art.

Our sketch posing tool is one of the few systems that

integrates 3D notions into the storyboarder’s work-

ﬂow in an intuitive way, while the majority of the ex-

isting tools tend to ignore the issue of 3D, or to impose

unnatural and complex interfaces. By following the

storyboarder’s constraints, we developed a tool that is

more suited to his needs. The user does not have to ro-

tate around the model to add more depth information,

unlike in (Guay, 2015)’s method. In addition, our tool

remains ﬂexible and adaptable, as it can be used with

various morphological types, unlike methods relying

on databases, such as (Akman et al., 2020). As op-

posed to (Gouvatsos, 2018)’s technique, our method

is automatic and works in real time. The originality

of our technique also comes from the combination of

several sketch abstractions integrated into three tools

that the user can pick instantly according to his needs.

In that way, our system can ﬁnd applications in

the 3D animation industry, as it would be particularly

suited to layout, previz and storyboard departments

where it could form a practical ideation tool.

7 CONCLUSIONS AND FUTURE

WORKS

Although this tool allows to quickly prototype poses,

it does not offer as many levels of precision as the

classical controller based technique, which affects the

quality of the resulting poses. Thus, some points

could be deepened in future works to improve our

method. For now, our sketch posing system doesn’t

consider how the character interacts with the 3D en-

vironment. As (Lin et al., 2012) did in their research,

we should try to implement new constraints in or-

der to avoid collisions with the other 3D objects of

the scene and use them to resolve depth ambigui-

ties. Moreover, our tool doesn’t take into account the

possible movements a character can do according to

his morphology, as described in some studies, such

as (Lee and Chen, 1985). Thus, in the future, we

will pursue the development of our work by adding

constraints to prevent the generation of implausible

poses. Finally, handling the case of facial expression

could be worthwhile. When our method will be sig-

niﬁcantly improved, we will have to make a better

study of its impact on the creative process by orga-

nizing testing sessions with storyboard artists and by

evaluating in a more relevant way the aesthetic and

technical quality of the resulting poses.

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132

ACKNOWLEDGEMENTS

We would like to thank Superprod Studio for giving

us the opportunity to experiment our tool on their 3D

asset (ﬁgures 2, 3, 7 and 8). We also thank the sto-

ryboarder and layout artists who agreed to participate

in our interviews and offered us important informa-

tion about their way of working. Finally, we thank

the Blender Foundation for the use of the Rain Rig to

test our system (ﬁgures 1 and 8).

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