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 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 IEEE FG as a single-track, one day event, to gather researchers on behavior analysis and analytics. It will have two specific focus sessions dealing with "face analytics" and "behavior analysis for smart cars".

Session 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.

Session 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

Session 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

Session 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
Program Committee
Tadas Baltrušaitis, Microsoft Corporation, UK
Wei Chen, China University of Mining and Technology, CN
Adrian Davison, University of Manchester, UK
Hamdi Dibeklioğlu, Bilkent University, TR
Jordi Gonzàlez, CVC Barcelona, ES
Jürgen Gall, Univ. of Bonn, DE
Heikki Huttunen, Tampere University of Technology, FI
Julian Kooij, Delft University of Technology, NL
Peng Liu, Aware, US
Marwa Mahmoud, Univ. of Cambridge, UK
Matei Mancas, Univ. of Mons, BE
Javier J. Sanchez Medina, ULPGC, ES
Teruhisa Misu, Honda Research Institute, US
Wenxuan Mou, Queen Mary University of London, UK
Eshed Ohn-Bar, Carnegie Mellon University, US
Shogo Okada, JAIST, JP
Yannis Panagakis, Imperial College London, UK
Senya Polikovsky, Max Planck Institute for Intelligent Systems, DE
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, Facebook, US
Mohan M. Trivedi, University of California San Diego, US
Ruiping Wang, Chinese Academy of Sciences, CN
Sujing Wang, Chinese Academy of Sciences, CN
Jacob Whitehill, Worcester Polytechnic Institute, US
Lijun Yin, University of Binghamton, US
Zeynep Yücel, Okayama University, JP

Organizers
Carlos Busso, Univ. of Texas at Dallas
Xiaohua Huang, Univ. of Oulu
Takatsugu Hirayama, Nagoya Univ.
Guoying Zhao, Univ. of Oulu & Northwest Univ. of China
Albert Ali Salah, Boğaziçi Univ. & Nagoya Univ.
Matti Pietikäinen, Univ. of Oulu
Roberto Vezzani, Univ. of Modena and Reggio Emilia
Wenming Zheng, Southeast Univ.
Abhinav Dhall, Indian Institute of Technology, Ropar