Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm
Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm
Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm
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<strong>Session</strong> WedET2 Fenix 2 <strong>Wednesday</strong>, <strong>October</strong> <strong>10</strong>, <strong>2012</strong>, 15:00–16:00<br />
Emotion Detection and Expression<br />
Chair C. S. George Lee, Purdue Univ.<br />
Co-Chair Ren Luo, National Taiwan Univ.<br />
15:00–15:15 WedET2.1<br />
An NARX-Based Approach for Human Emotion<br />
Identification<br />
Rami Alazrai and C.S. George Lee<br />
School of Electrical and Computer Engineering, Purdue University, U.S.A<br />
• Propose an NARX-based approach to<br />
capture the spatial and temporal dynamics<br />
of facial expressions.<br />
• Temporal phases of facial expressions are<br />
identified using the proposed MIBDIA<br />
algorithm.<br />
• The proposed human-emotion recognition<br />
system achieved 91.5% average<br />
recognition rate over the CK+ dataset.<br />
15:30–15:45 WedET2.3<br />
Development of Expressive Robotic Head<br />
for Bipedal Humanoid<br />
Robot<br />
Tatsuhiro Kishi, Takuya Otani, Nobutsuna Endo,<br />
Przmyslaw Kryczka, Kenji Hashimoto, Kei Nakata<br />
and Atsuo Takanishi<br />
Faculty of Science and Engineering, Waseda University, Japan<br />
• Robotic head was developped to increase<br />
the facial expression ability of bipedal<br />
humanoid robot.<br />
• Representative facial expressions for 6<br />
basic emotion were designed by<br />
cartoonists.<br />
• Compact Mechanisms were developped to<br />
build the robotic head as small as<br />
Japanese female’s head.<br />
• Evaluations with pictures and videos show<br />
that the robotic head has extensive facial<br />
expression ability.<br />
15:15–15:30 WedET2.2<br />
A Design Methodology for<br />
Expressing Emotion on Robot Faces<br />
Mohammad Shayganfar, Charles Rich and Candace L. Sidner<br />
Computer Science Dept<br />
Worcester Polytechnic Institute, USA<br />
• Methodology is grounded in the<br />
psychological literature (Ekman FACS)<br />
• Four steps: (i) assign action units to robot<br />
DOF, (ii) apply mapping from basic action<br />
units to emotions, (iii) predict confusions,<br />
(iv) add optional action units and cartoon<br />
ideas to reduce confusion<br />
• Demonstrated and evaluated by applying<br />
methodology to a recent humanoid robot<br />
(see figure)<br />
• The experimentaly observed emotion<br />
confusion matrix agrees qualitatively with<br />
the predictions of the methodology<br />
15:45–16:00 WedET2.4<br />
Confidence Fusion Based Emotion Recognition<br />
of Multiple Persons for Human-Robot Interaction<br />
Ren C. Luo, Pei Hsien Lin, Li Wen Chang<br />
Center for Intelligent Robotics and Automation Research, National Taiwan University<br />
• We propose an integrated system which<br />
has the ability to track multiple users at one<br />
time, to recognize their facial expressions,<br />
and to identify the indoor ambient<br />
atmosphere.<br />
• In our facial expression recognition<br />
scheme, we fuse Feature Vectors based<br />
Approach (FVA) and Differential-Active<br />
Appearance Model Features based<br />
Approach (DAFA) to obtain not only<br />
apposite positions of feature points, but<br />
also more information about texture and<br />
appearance.<br />
• With our system, our intelligent robot with<br />
vision systems are able to acquire the<br />
ambient atmosphere information and<br />
interacts with people properly.<br />
<strong>2012</strong> IEEE/RSJ International Conference on Intelligent Robots and Systems<br />
–162–<br />
A surprise situation of humanrobot<br />
interaction