Expressive Human Pose Deformation Based on
the Rules of Attractive Poses
Masaki Oshita, Kei Yamamura, and Aoi Honda
Kyushu Institute of Technology
680-4 Kawazu, Iizuka, Fukuoka, 820-8502, Japan{oshita,aoi}@ces.kyutech.ac.jp,yamamura@cg.ces.kyutech.ac.jp
Abstract. We propose a method of deforming a human pose based on
the rules of attractive poses. In our previous research, we proposed an approach for obtaining the rules of attractive poses from a set of attractive
poses with a speciﬁc style and another set of unattractive poses by creating a decision tree based on the low-level pose features. In this paper, we
propose a heuristic kinematics-based pose deformation method based on
the discovered rules of attractive poses. The rules can be applied to any
input pose with any speciﬁed scale. We evaluated our method through auser experiment. The results show that our method can deform a poseto realize a speciﬁed style, although not all rules are applicable to allkinds of poses and an appropriate style and deformation scale must be
selected by the user.
Key words: human pose, attractive poses, pose deformation

1 Introduction
Attractive poses of human characters often appear in various types of media
content such as movies, animations, computer games, illustrations, comics, andaction ﬁgures. The creators must design attractive poses that fall within a certainstyle and are novel and eye-catching. Because there are no speciﬁc deﬁnitions orrules of attractive poses, the creators must design them based on their experienceand through trial and error. This is a diﬃcult and time-consuming task.
In our previous research [1], we proposed an approach to obtain the rulesof attractive poses from a set of attractive poses with a speciﬁc style and another set of unattractive poses by creating a decision tree based on the low-level
pose features that are computed from the example poses. We implemented ourapproach for two kinds of attractive poses, Hero and JoJo standing poses, andsuccessfully discovered the rules of these styles. We also developed a heuristic
pose deformation method specialized for the discovered rules.
In this paper, we propose a method of deforming a human pose. We developed
a heuristic kinematics-based pose deformation method based on the discovered
rules of attractive poses. This method is generalized and can work with any rules
based on our low-level pose features. The rules can be applied to any input posewith any speciﬁed scale. Using our system, a creator can interactively design

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(a) pose deformation mode(b) user experiment mode

Fig. 1. Developed pose deformation system. (a) The pose deformation mode allows theuser to apply the rules of attractive poses to an input pose. The input pose is shown on
the left side. The deformed (output) pose is shown on the right side. The class (styleand category) of attractive poses is selected via the menu at the bottom. Whether the
input pose satisﬁes the rules of the class is shown on the top left by a circle (yes) or across (no). The deformation scale is controlled by the slider on the top right. (b) The
user experiment mode shows a randomly selected example pose and a deformed pose.
The user is asked which pose has the indicated style.

novel poses. We evaluated our method in a user experiment. The results showthat our method can deform a pose to realize a speciﬁed style, although not all
rules are applicable to all kinds of poses and an appropriate style and deformation
scale must be selected by the user.
Attractiveness is an important factor in content creation. However, it is adiﬃcult factor to evaluate. Although there are subjective evaluations for human motions [2], the speciﬁc rules of attractiveness are still unclear. In thisresearch, we developed a pose deformation method based on the rules of attractive poses that we discovered in our previous work [1]. For pose deformation,
we implemented a kinematics-based method. Although similar approaches havebeen used before [3, 4], our method focuses on the pose features that appear
in the discovered rules of attractive poses. High-level pose features have been
introduced in previous studies [5]. However, such high-level features are only
applicable to a speciﬁc range of poses. To handle a wide range of poses, manypose features would be required.

2 System Overview
We have developed a pose deformation method and system. Figure 1 shows
screen shots of our system. The user can specify an input pose, a class of attractive poses, and a deformation ratio. The system deforms the input poseinteractively. An input pose can be speciﬁed in several ways. The system has auser experiment mode that we implemented for our experiments. This mode is
explained in Section 5.1.

Expressive Human Pose Deformation

3

Given a human skeleton model, a pose is represented by the position androtation of the pelvis and the rotations of all joints. We used a skeleton modelwith 16 joints and 15 segments. A skinned human model is used to display poses,
as shown in Figure 1. Our system provides several ways to input a pose such as
the use of a mouse-based pose editing interface [1].

3 Rules of Attractive Poses
In this section, we brieﬂy explain the rules of attractive poses for two kinds ofexample poses. For the details, the reader can refer to our previous work [1].
We deﬁne each type of attractive pose using examples. Given a set of attractive poses with a speciﬁc style and another set of unattractive poses, we
determined rules with which to separate the two sets of poses by creating a decision tree. Our research focuses on the static standing poses of a male characterwith an average physique who does not hold any props. We also assume that theattractiveness of a pose is view independent and it does not change when thepose is mirrored (i.e., ﬂipped horizontally).
3.1 Pose Features
We compute a large number of low-level pose features for each example pose(381 in total). Of them, a decision tree automatically chooses a few importantfeatures that are eﬀective for separating attractive and unattractive poses.
We use simple pose features such as the positions and orientations of the bodysegments and joints that can be computed from the pose representation using
forward kinematics. All pose features are represented by a (signed or unsigned)
one-dimensional scalar value . Three-dimensional positions and rotations are
divided into a combination of single variables.
As mentioned above, the attractiveness of a pose should not change when
the pose is mirrored (i.e., ﬂipped horizontally). Therefore, instead of using posefeatures from the right and left sides (limbs) of the pose, we use the average
and absolute diﬀerence between values from the two sides. Additionally, as thehorizontal position and direction of the pose do not aﬀect the attractiveness ofthe pose, horizontal positions and angles are discarded. The pose features are
categorized as follows.
1. Rotational angles of the center joints
2. Rotational angles of the limb joints (the average and diﬀerence angles of theright and left side joints).
3. Relative orientation angles between the center body segments.
4. Orientation of the center body segments with respect to the ground.
5. Body segment heights
6. Body segment distances
7. Height of the center of mass

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Fig. 2. Examples of attractive Hero poses
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Fig. 3. Examples of attractive JoJo poses
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Fig. 4. Examples of unattractive poses

3.2 Example Pose Sets
We implemented our approach for two styles of attractive poses: Hero and JoJo
styles. We chose these two styles because they are well-known popular styles
in Japanese culture and materials such as picture and illustration books about
these styles are available.
We created 30 example attractive poses for each style based on example posesthat are taken from the picture and illustration books. In addition, we created
30 examples of unattractive poses.

Expressive Human Pose Deformation

5

Hero poses (Figure 2) are the ﬁrst type of attractive pose used in this study.
Suited action heroes in Japanese movies often appear in Hero poses. When ahero or heroine faces the villain during a ﬁght scene, they often adopt strong
and deﬁant poses. The example poses are chosen from a picture book [6] that ismeant to provide examples for creators.
JoJo poses (Figure 3) are the other type of attractive pose considered inthis study. The JoJo standing poses appear in the comic series JoJo’s Bizarre
Adventure by Hirohiko Araki [7], which is famous and popular in Japanese culture. The JoJo standing poses have a unique style. They are often imitated inmany other media as well. The example poses were chosen from an illustration
book [8].
Unattractive poses (Figure 4) are ordinary standing poses. They werechosen from various books [9, 10]. Of the many possible example poses, weselected ordinary poses that are dissimilar to the Hero and JoJo poses.
3.3 Discovered Rules of Attractive Poses
Decision trees are a non-parametric supervised learning method used for classiﬁcation [11, 12]. The results are represented as simple trees, which are visible
and easy interpreted. By changing a parameter that determines the processing
condition, diﬀerent trees with similar accuracies can be generated. We chose adecision tree that contains fewer pose features and conditions and provides intuitive rules. Some styles have more than one category of poses. The rules forﬁve classes (style and category) were obtained as follows.
Hero Poses Almost all of the Hero poses can be categorized into one clusterwith conditions as follows.
Hero pose: The bending angle of head with respect to the neck should be
between −0.045 and 0.15. If the bending angle is between 0.15 and 0.045, theabsolute value of the horizontal angles of the head with respect to the trunk
and waist should be less than 0.11 and 0.77, respectively. In short, when boththe bending and orientation angles of the head are small (i.e., the head is facing
forward), the pose is considered to be a good pose.
JoJo Poses JoJo poses are categorized into four clusters as follows.
JoJo pose A: When the bending angle of the trunk with respect to theground is less than −0.063 (i.e., bent backward), the bending angle of the headwith respect to the pelvis should be should be less than 0.22. In short, when
the trunk is bent backward, the bending angle of the head should be straight.
Typical poses in this category are poses 1 and 24 in Figure 3.
JoJo pose B : When the bending angle of the trunk with respect to theground is between −0.063 and 0.46 (i.e., straight), the absolute value of thediﬀerence between the bending angles of the left and right knees should be larger
than 0.59. In short, when the trunk is straight, the bending angles of the knees
should be asymmetrical. Typical poses are poses 9 and 16 in Figure 3.

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JoJo pose C : When the bending angle of the trunk with respect to theground is between −0.063 and 0.46 (i.e., straight) and the absolute value of thediﬀerence between the bending angles of the left and right knees is smaller than
0.59, the absolute value of the horizontal orientation of the neck with respect
to the trunk should be between 0.0078 and 0.01. In short, when the trunk isstraight, the head should be facing forward. Typical poses are poses 11 and 26
in Figure 3.
JoJo pose D : When the bending angle of the trunk with respect to theground is larger than 0.46 (i.e., bent forward), the absolute value of the diﬀerence
between the bending angles of the left and right elbows should be larger than
0.15. In short, when the trunk is bent backward, the bending angles of the elbows
should be asymmetrical. Typical poses are poses 12 and 29 in Figure 3.

4 Pose Deformation
We developed a pose deformation method based on the discovered rules of attractive poses. The rules can be applied to any input pose with any speciﬁed
scale. We deﬁned pose deformation parameters based on the pose features thatare used in the rules. Using these parameters, an input pose can be deformed
using a heuristic kinematics-based method.
4.1 Adjusting Pose Features
The target values of the pose features are determined according to the selectedstyle and category and the speciﬁed scale of attractiveness. As the scale increases,
each target pose value approaches to the desirable range and value in the thediscovered rules. When the scale is between 0.0 and 0.5, it is linearly interpolated
from the initial value, which is computed from the initial pose to the thresholdusing the discovered rules. When the scale is between 0.5 and 1.0, it is linearlyinterpolated from the threshold to an extreme value that is manually speciﬁed
in advance. If the rules deﬁne a feature range, the center of the range is used as
the extreme value.
4.2 Pose Deformation
Given an input pose and desired pose features, the input pose is deformed
through the following three steps.
Step 1. Deformation of the upper-body pose Joint rotations of the upperbody joints and the pelvis are computed. Joint rotations, segment orientations,and segment positions can be controlled by one or a few joint rotations. When thepose feature is mapped to a single joint rotation, the joint rotation is determinedaccording to the desired pose feature value. When the pose feature is mapped tomultiple joint rotations, the rotations of these joints are computed according toExpressive Human Pose Deformation7

the desired pose feature value and the weights of joints that are manually deﬁned
in a way similar to [13]. The head orientation, for example, can be controlled byrotations of the neck, trunk, and pelvis. When there are multiple conditions that
control the same joint, the order of conditions must be determined manually.
Step 2. Balance correction control Deformation of the upper-body pose
may result in an unbalanced pose. The lower body pose is controlled throughthe position of the pelvis. All joint rotations on both legs are computed using
inverse kinematics [14] so that the positions of both feet are kept. The horizontal(two-dimensional) position of the pelvis is computed to keep the balance so thatthe horizontal position of the center of mass remains in the same place after
deformation of the upper-body pose .
Step 3. Deformation of the lower-body pose The lower body pose iscontrolled via the lateral (one-dimensional) position of the pelvis under the constraints of balance and foot position. The lateral axis is determined according
to the positions of the two feet. Balance can be maintained as long as the pelvis
moves along the lateral axis. The target lateral position is linearly interpolated
between the initial value and foot position.
The pose features contain the rotations of the lower-body joints. However,
it is not possible to simply change them, because such pose deformation breaks
the constraints of contact between the feet and ground. We therefore control
them by moving the pelvis along the lateral axis; e.g., the diﬀerence between thebending angles of the two knees is controlled. When the pelvis is moved over theright foot, the right knee is bent and the left knee is extended. Note that therequired pose feature may not be satisﬁed depending on the input pose. Whenthe two feet are close to each other, for example, there is little room in whichto control the lateral pelvis position without moving the foot positions. This isa limitation of our method.

5 Experimental Results and Discussion
5.1 User experiment
We conducted a short user experiment to evaluate the eﬀectiveness of our posedeformation method and the discovered rules of attractive Hero and JoJo poses.
We evaluated whether the subjects could recognize that the poses deformed using our method have the intended styles compared with the original poses. Nine
university students participated in the experiment. The participants were moderately familiar with Japanese subcultures including Hero and JoJo, although
they were not content creators. Before the user experiment, images of example
poses of Hero and JoJo (Figures 2 and 3) were presented to each participant sothat they could grasp the features of these styles. During the experiment, oursystem randomly chose an example pose from the set of 30 ordinary poses, aclass of attractive poses from ﬁve classes (style and category), and a deformation scale from 0.5 or 1.0. There were thus 300 combinations (patterns). The

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Masaki Oshita et al.
90% - 100%80% - 90%0%0% - 10%
10% - 20%
20% - 30%

70% - 80%

30% - 40%

60% - 70%

50% - 60%

40% - 50%

Fig. 5. Results of our user experiment. A histogram of all 300 patterns based on theratios of answers that correctly chose the deformed pose matches the indicated styleover the original pose.

system showed the original example pose and the deformed pose for a random
placement as shown in Figure 1 (b). The participant was then asked to choose
which pose has the indicated style compared with the other other pose. The participant could change the viewing orientation of the pose using a mouse. Eachparticipant went through 300 trials, which took about 30 minutes.
5.2 Results and Discussion
We measured whether the participants chose the deformed pose correctly foreach pattern of example pose, class and deformation scale. Because this is a
two-choice question, the ratio of correct answers should be around 50%, if ourpose deformation method is ineﬀective. The results are shown in Figure 5. Highaccuracy ratios exceeding 70% were obtained for 24.66% of patterns. This demonstrates that our method can realize the intended style successfully on many patterns. Meanwhile, a low accuracy ratio less than 30% was obtained for 14.0%
of patterns. This shows that the combination of an input pose and a class isimportant, in that some combinations could have negative eﬀects. However, thisis not a problem in practice for our system. As the user can choose the class anddeformation scale interactively, they can avoid such ineﬀective combinations.
Examples of successful and unsuccessful patterns are shown in Figure 6 and7, respectively. We analyzed some unsuccessful examples to see why our deformation method had negative eﬀects. One reason that we found was the problem ofincomplete rules of attractive poses. For example, in Figure 7 (g), the head faces
down in the deformed pose, whereas Hero poses are expected to have the headfacing forward. This is because our rules of Hero poses happened to be basedon the local neck rotations and keep it straight. When the body faces down, thehead faces down too. This kind of problem should be avoided by reﬁning thedecision trees.
Another reason that we found was the problem of local pose deformation.
As our deformation method only deals with a small part of the pose without
considering the full body, infeasible poses may be produced. In Figure 7 (h), forExpressive Human Pose Deformation

input
output(a) application of Hero pose rules

input
output(b) application of JoJo pose A rules

input
output(c) application of JoJo pose B rules

input
output(d) application of JoJo pose C rules

input
output(e) application of JoJo pose D rules

input
output(f) application of JoJo pose B rules

9Fig. 6. Examples of successful pose deformation. Rules of the selected type and category are applied to the input.

input
output(g) application of Hero pose rules

input
output(h) application of JoJo pose D rules

input
output(i) application of JoJo pose A rules

Fig. 7. Examples of unsuccessful pose deformation.

example, the deformation method extends the right arm and bends the left arm
without considering shoulder rotations and collisions. As a result, the right arm
pose looks infeasible and the left arm penetrates into the body. In Figure 7 (i),the upper body is too bent and the resulting pose looks infeasible. As explained
in section 4.1, we set extreme motion feature values manually. By setting smaller
extreme values, such a problem does not happen. However, some poses may needhigher extreme values. As mentioned above, this is not a problem in practice,as the user can interactively control the deformation scale to avoid deformation
parameters that are too large and infeasible poses.
We successfully applied our approach to small numbers of example Heroand JoJo poses. Our pose deformation should be applicable to other rules fordiﬀerent kinds of attractive poses as long as the rules are described according
to the low-level pose features. We are planning to implement our approach toa wider range of attractive poses. Introducing more advanced pose features isalso a possible future direction of research. However, pose deformation becomesa diﬃcult problem, because human poses have more degrees of freedom and it ishard to make a reasonable pose on the basis of a small number of pose features.

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6 Conclusion
We developed a heuristic kinematics-based pose deformation method based on
the discovered rules of attractive poses. We evaluated our method through auser experiment. The results show that our method can deform a pose to realize
a speciﬁed style. Although we still need to experiment on diﬀerent types of attractive poses, we believe that our approach is promising and can be an eﬀective
way to create novel attractive poses.

Acknowledgment
This work was supported in part by Grant-in-Aid for Scientiﬁc Research (No.
15H02704 and No. 15K05003) from the Japan Society for the Promotion of
Science (JSPS).

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