<html> <head> <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-3"> <style type="text/css" style="display:none;"> P {margin-top:0;margin-bottom:0;} </style> </head> <body dir="ltr"> <div style="font-family: Calibri, Arial, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255);"> [Apologies for cross-posting] </div> <div dir="ltr"> <div class="x_elementToProof" style="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255);"> *********************************************************************************************** CALL FOR PAPERS - DEADLINE EXTENDED - HBU 2022 12th International Workshop on Human Behavior Understanding (HBU) Focus theme: Applications for Clinical and Behavioral Sciences Held in conjunction with <a href="https://www.icpr2022.com/" data-auth="NotApplicable">ICPR 2022</a> Workshop website: <a href="https://www.cmpe.boun.edu.tr/hbu/2022/" data-auth="NotApplicable">https://www.cmpe.boun.edu.tr/hbu/2022/</a> Paper submission deadline: June 6th, 2022 [EXTENDED] Notifications: July 6th, 2022 [EXTENDED] <p dir="ltr" style="font-family: Calibri, Arial, Helvetica, sans-serif; font-size: 12pt; line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt; background-color: rgb(255, 255, 255);" class="elementToProof"> Camera-ready submission deadline: September 6th, 2022 [UPDATED BY ICPR ORGANIZERS] Workshop: August 21st, 2022 *********************************************************************************************** ORGANIZERS Albert Ali Salah, Universiteit Utrecht, Netherlands, and Bo»aziçi University, Turkey Sergio Escalera, Universitat de Barcelona and Computer Vision Center, Spain Cristina Palmero, Universitat de Barcelona and Computer Vision Center, Spain Henning Müller, HES-SO, Switzerland Hugo Jair Escalante, Instituto Nacional de Astrofísica, Óptica y Electrónica, México ABOUT Domains for human behavior understanding (e.g. multimedia, human-computer interaction, robotics, affective computing and social signal processing) predominantly rely on advanced pattern recognition techniques to automatically interpret complex behavioral patterns generated when humans interact with machines or with other agents. This is a challenging research area where many issues are still open, including the joint modeling of behavioral cues taking place at different time scales, the inherent uncertainty of machine detectable evidences of human behavior, the mutual influence of people involved in interactions, the presence of long term dependencies in observations extracted from human behavior, and the important role of dynamics in human behavior understanding. For clinical and behavioral sciences, not only accurate behavior analysis is essential, but further aspects like explainability, privacy-aware processing, and fairness are often required. The development of explainable and interpretable models for social behavior analysis would result in more trustable solutions that could be adopted by domain experts for informed decision making. Furthermore, public datasets are often difficult to obtain and share in a privacy-aware manner (particularly during Covid-19), which hampers scientific progress. This workshop, organised as part of <a href="https://www.icpr2022.com/" data-auth="NotApplicable">ICPR 2022</a>, will gather researchers dealing with the problem of modeling human behavior under its multiple facets (expression of emotions, display of relational attitudes, performance of individual or joint actions, etc.), with particular attention to clinical settings and tools usable for behavioral scientists. Examples of challenges are automatic labeling, annotation, and reporting systems, datasets acquired from real or simulated clinical conditions, systems that focus on the analysis of interaction dynamics, early diagnosis and intervention systems, augmented telepresence, personalized agents, and multimodal approaches. The HBU workshops, previously organized as satellite events to major conferences in different disciplines (ICPR'10, AMI'11, IROS'12, ACMMM'13, ECCV'14, UBICOMP'15, ACMMM'16, FG'18, ECCV'18, ICCV'19, WACV'21) have a unique aspect of fostering cross-pollination of disciplines, bringing together researchers from a variety of fields, such as computer vision, pattern recognition, HCI, artificial intelligence, interaction design, ambient intelligence, social signal processing, psychology, and robotics. The diversity of human behavior, the richness of multimodal data that arises from its analysis, and the multitude of applications that demand rapid progress in this area ensure that the HBU Workshops provide a timely and relevant discussion and dissemination platform. TOPICS OF INTEREST The topics for submission include all papers relevant to the automatic analysis and modeling of human behavior. These include, but are not limited to: <ul style="font-family: Calibri, Arial, Helvetica, sans-serif; font-size: 12pt; font-weight: normal; margin-top: 0px; margin-bottom: 0px;"> <li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Applications of human behavior analysis for clinical and behavioral sciences </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Explainable and interpretable models for the analysis of human behavior </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Detection, understanding, modeling and synthesis of individual and interpersonal social signals and dynamics </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Verbal / nonverbal communication analysis </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Contextual analysis in interpersonal interactions </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Datasets, annotation protocols and bias discovering/mitigation methods </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Multimodal human behavior analysis </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Fairness in human behavior analysis </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Privacy-aware processing of human behavior </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Clinical datasets and validity </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Social behaviour analysis </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Affective computing </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Human-computer interaction </li><li dir="ltr" style="font-size: 11pt; font-family: Arial; font-weight: 400; color: rgb(0, 0, 0);"> Behavioral biometrics </li></ul> INVITED SPEAKERS Juan Wachs, Purdue University, USA Ehsan Hoque, University of Rochester, USA Rich Caruana, Microsoft Research, USA PAPER SUBMISSION Submission instructions can be found at <a href="https://www.cmpe.boun.edu.tr/hbu/2022/submission.html" data-auth="NotApplicable">https://www.cmpe.boun.edu.tr/hbu/2022/submission.html</a> Please feel free to reach out for further details. Albert Ali Salah, Sergio Escalera, Cristina Palmero, Henning Müller, Hugo Jair Escalante HBU 2022 Organizers </div> </div> Aquest missatge, i els fitxers adjunts que hi pugui haver, pot contenir informació confidencial o protegida legalment i s’adreça exclusivament a la persona o entitat destinatària. Si no consteu com a destinatari final o no teniu l’encàrrec de rebre’l, no esteu autoritzat a llegir-lo, retenir-lo, modificar-lo, distribuir-lo, copiar-lo ni a revelar-ne el contingut. Si l’heu rebut per error, informeu-ne el remitent i elimineu del sistema tant el missatge com els fitxers adjunts que hi pugui haver. Este mensaje, y los ficheros adjuntos que pueda incluir, puede contener información confidencial o legalmente protegida y está exclusivamente dirigido a la persona o entidad destinataria. Si usted no consta como destinatario final ni es la persona encargada de recibirlo, no está autorizado a leerlo, retenerlo, modificarlo, distribuirlo o copiarlo, ni a revelar su contenido. 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