News
May 20, 2018: Our new work about group-level happiness intensity estimation (submitted to IEEE Transactions on Affective Computing, under revision) is available in arXiv (preview version, but the final version will be updated in future).
May 20, 2019: One joint paper (title: Going beyond what is visible: what multichannel data can reveal about interaction in the context of collaborative learning?) is available in Computers in Human Behavior.
May 17, 2019: Received the Outstanding Reviewer Award at IEEE International Conference on Automatic Faces & Gesture Recognition 2019, Lille, France.
April 10, 2019: Our work (Interactive facial emotion recognition game for children with autism, Jim Gribble from UC-Santa Barbara, USA, Prof. Guoying Zhao from University of Oulu and Xiaohua Huang from University of Oulu) has been accepted as a paper presentation at: University of California, Berkeley’s Annual Education Research Day.
November 29, 2017
Our special issue proposal on Automatic face analytics for human behavior understanding was accepted by Image and Vision Computing Journal. Welcome to submit your new research to our special issue. Additionally, the workshop papers appeared in FaceHUB workshop in conjunction with BMVC2017 and FG2018 will be encouraged to extend it. The detail about paper submission about special issue will be announced later.
November 1, 2017
CALL FOR PAPERS: 8th Int. Workshop on Human Behavior Understanding (HBU)
in conjunction with 2nd Int. Workshop on Automatic Face Analytics for Human
Behavior Understanding (FaceHUB) at IEEE Face & Gesture 2018 - Xi'An, 15-19
May 2018
https://www.cmpe.boun.edu.tr/hbu/2018/
Workshop Description
With development of computer vision and sensor technology, it becomes
possible to analyze human behavior via various ways at different time-scales
and at different levels of interaction and interpretation. Understanding
human behavior automatically opens up enormous possibilities for
human-computer interaction, with a potential of endowing the computers with
a capacity to attribute meaning to users' attitudes, preferences,
personality, social relationships, etc., as well as to understand what
people are doing, the activities they have been engaged in, and their
routines.
This workshop aims to inspect developments in selected areas where smarter
computers that can sense human behavior have great potential to
revolutionize the application domain. We ultimately seek to re-define the
relationship between the computer and the interacting human, moving the
computer from a passive observer role to a socially active participant role
and enabling it to drive different kinds of interaction.
The 8th Int. Workshop on Human Behavior Understanding (HBU) and 2nd Int.
Workshop on Automatic Face Analytics for Human Behavior Understanding
(FaceHUB) are jointly organized at FG to gather researchers on behavior
analysis and analytics. It will have two specific focus tracks dealing with
"face analytics" and "behavior analysis for smart cars".
Track 1 "Face analytics": There is strong evidence that face analytic for
human behavior understanding could also be highly beneficial in human
computer interaction. Application scenarios include analyzing emotions while
the person is watching emotional movies or advertisements, playing video
games, driving a car, is under health monitoring or crime investigation, or
is participating in interactive tutoring. Furthermore, long-term continuous
monitoring and analysis of expressions provides important information for
assessing personality but also provide cues of psychological disorders.
Track 2 "Behavior analysis for smart cars": The computational capabilities
of cars are rapidly increasing. While a lot of attention is directed towards
what goes on outside the car, and to autonomous driving systems, the inside
of the car is very interesting too. In the transition period from
human-driven cars to fully autonomous cars, there is great interest in
improved driver assistance, safety, and comfort systems. When the fully
autonomous car is realized, there will still be a need for looking inside
the car, for better car-customer interaction.
This workshop will solicit human behavior analysis solutions that clearly
advance the field, and also to propose novel application scenarios. The
covered topics may span items from the following topic dimensions, as well
as target a focus theme challenge:
Human Behavior Analysis Systems
*******************************
Action and activity recognition
Single and multimodal affect analysis
Gaze, attention and saliency
Gestures and haptic interaction
Learning and adaptation
Social signal processing
Voice and speech analysis
Theory and Methodology of Human Interactive Behaviors
*****************************************************
Data collection, annotation, and benchmarking
Interaction design
Theoretical frameworks of behavior analysis
User studies and human factors
Track 1: Face analytics
***********************
Automatic deception detection
Deep learning models for facial analysis
Face alignment and fiducial point detection
Continuous and dynamic facial behavior analysis
Emotion recognition in the wild
Temporal models for face analysis
Facial action unit detection and recognition
Group emotion analysis
Long-term behaviors and interaction
Micro-expression detection, recognition and understanding
Spontaneous affect databases: collection and annotation
Cross-domain facial expression recognition
Spontaneous facial expression analysis
Multimodal emotion recognition
Track 2: Behavior analysis for smart cars
*****************************************
Advanced driver assistance systems, assisting elderly drivers
Behavior analysis for car safety
Car driving simulation analysis
Driver identification and biometrics
Driver's face monitoring, drowsiness and fatigue detection
Head pose and attention tracking
Human factors and driver personalization
Human-car interaction
In-car social signals: aggression, frustration, boredom
Multimodal interactive systems in cars
Posture assessment and comfort analysis
Submission
Submission site is open, and accessible at:
https://easychair.org/conferences/?conf=hbu2018
Each paper will be reviewed by at least two members of the scientific
Program Committee, in double-blind fashion. The submitted papers should
present original work, not currently under review elsewhere and should have
no substantial overlap with already published work. Submissions should be
submitted in PDF and should be no more than 8 pages in IEEE FG 2018 paper
format. Accepted papers will be included in the Proceedings of IEEE FG 2018
and Workshops and will be sent for inclusion into the IEEE Xplore digital
library.
Dates
28 January, Submission deadline
20 February, Notification of acceptance
1 March, Camera ready submission
15 May, Tentative workshop date
Special Issues
Two journal special issues are planned from the two focus tracks of the
HBU Workshop. One issue on `behavior analysis for smart cars` will be edited
as a thematic issue of Journal of Ambient Intelligence and Smart
Environments. A second issue on `face analytics` is planned. Authors will be
invited to submit suitably extended versions of their papers to these
special issues.
People
Organizers
Carlos Busso, Univ. of Texas at Dallas
Xiaohua Huang, Univ. of Oulu (1)
Takatsugu Hirayama, Nagoya Univ.
Guoying Zhao, Univ. of Oulu & Northwest Univ. of China
Albert Ali Salah, Bogaziçi Univ. & Nagoya Univ. (2)
Matti Pietikäinen, Univ. of Oulu
Roberto Vezzani, Univ. of Modena and Reggio Emilia
Wenming Zheng, Southeast Univ.
Abhinav Dhall, Indian Institute of Technology
(1) Contact for Track 1 and The workshop on Automatic Face Analytics for
Human Behavior Understanding
(2) Contact for Track 2
Tentative Program Committee
(being formed at the moment, only confirmed members listed)
Tadas Baltrušaitis, CMU, US
Wei Chen, China University of Mining and Technology, CN
Adrian Davison, University of Manchester, UK
Hamdi Dibeklioglu, Bilkent University, TR
Jordi Gonzàlez, CVC Barcelona, ES
Jürgen Gall, Univ. of Bonn, DE
Heikki Huttunen, Tampere University of Technology, FI
Peng Liu, Aware, US
Marwa Mahmoud, Univ. of Cambridge, UK
Matei Mancas, Univ. of Mons, BE
Javier J. Sanchez Medina, CVC-UAB, ES
Teruhisa Misu, Honda Research Institute, US
Wenxuan Mou, Queen Mary University of London, UK
Eshed Ohn-Bar, CMU, US
Shogo Okada, JAIST, JP
Yannis Panagakis, Imperial College London, UK
Senya Polikovsky, Max Planck Institute for Intelligent Systems, JP
Nicu Sebe, University of Trento, IT
Caifeng Shan, Philips Research, NL
Karan Sikka, Stanford Research Institute, US
Xiaoyang Tan, Nanjing University of Aeronautics and Astronautics, CN
Yan Tong, University of South Carolina, US
Fernando De la Torre, CMU, US
Mohan M. Trivedi, UCSD, US
Ruiping Wang, Chinese Academy of Sciences, CN
Sujing Wang, Chinese Academy of Science, CN
Jacob Whitehill, Worcester Polytechnic Institute, US
Lijun Yin, University of Binghamton, US