Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm

Session WedET2 Fenix 2 Wednesday, October 10, 2012, 15:00–16:00
Emotion Detection and Expression
Chair C. S. George Lee, Purdue Univ.
Co-Chair Ren Luo, National Taiwan Univ.
15:00–15:15 WedET2.1
An NARX-Based Approach for Human Emotion
Identification
Rami Alazrai and C.S. George Lee
School of Electrical and Computer Engineering, Purdue University, U.S.A
• Propose an NARX-based approach to
capture the spatial and temporal dynamics
of facial expressions.
• Temporal phases of facial expressions are
identified using the proposed MIBDIA
algorithm.
• The proposed human-emotion recognition
system achieved 91.5% average
recognition rate over the CK+ dataset.
15:30–15:45 WedET2.3
Development of Expressive Robotic Head
for Bipedal Humanoid
Robot
Tatsuhiro Kishi, Takuya Otani, Nobutsuna Endo,
Przmyslaw Kryczka, Kenji Hashimoto, Kei Nakata
and Atsuo Takanishi
Faculty of Science and Engineering, Waseda University, Japan
• Robotic head was developped to increase
the facial expression ability of bipedal
humanoid robot.
• Representative facial expressions for 6
basic emotion were designed by
cartoonists.
• Compact Mechanisms were developped to
build the robotic head as small as
Japanese female’s head.
• Evaluations with pictures and videos show
that the robotic head has extensive facial
expression ability.
15:15–15:30 WedET2.2
A Design Methodology for
Expressing Emotion on Robot Faces
Mohammad Shayganfar, Charles Rich and Candace L. Sidner
Computer Science Dept
Worcester Polytechnic Institute, USA
• Methodology is grounded in the
psychological literature (Ekman FACS)
• Four steps: (i) assign action units to robot
DOF, (ii) apply mapping from basic action
units to emotions, (iii) predict confusions,
(iv) add optional action units and cartoon
ideas to reduce confusion
• Demonstrated and evaluated by applying
methodology to a recent humanoid robot
(see figure)
• The experimentaly observed emotion
confusion matrix agrees qualitatively with
the predictions of the methodology
15:45–16:00 WedET2.4
Confidence Fusion Based Emotion Recognition
of Multiple Persons for Human-Robot Interaction
Ren C. Luo, Pei Hsien Lin, Li Wen Chang
Center for Intelligent Robotics and Automation Research, National Taiwan University
• We propose an integrated system which
has the ability to track multiple users at one
time, to recognize their facial expressions,
and to identify the indoor ambient
atmosphere.
• In our facial expression recognition
scheme, we fuse Feature Vectors based
Approach (FVA) and Differential-Active
Appearance Model Features based
Approach (DAFA) to obtain not only
apposite positions of feature points, but
also more information about texture and
appearance.
• With our system, our intelligent robot with
vision systems are able to acquire the
ambient atmosphere information and
interacts with people properly.
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
–162–
A surprise situation of humanrobot
interaction