Challenges of Human Behavior Understanding -- Challenges of Human Behavior Understanding -- Analysis of Human Activities -- Understanding Macroscopic Human Behavior -- Activity-Aware Map: Identifying Human Daily Activity Pattern Using Mobile Phone Data -- From On-Going to Complete Activity Recognition Exploiting Related Activities -- Human Activity Recognition Using Inertial/Magnetic Sensor Units -- Non-verbal Action Dynamics -- Face Tracking and Recognition Considering the Camera’s Field of View -- Spatiotemporal-Boosted DCT Features for Head and Face Gesture Analysis -- Concensus of Self-features for Nonverbal Behavior Analysis -- Visual Action Recognition -- Recognizing Human Action in the Wild -- Comparing Evaluation Protocols on the KTH Dataset -- 3D Mean-Shift Tracking of Human Body Parts and Recognition of Working Actions in an Industrial Environment -- Feature Representations for the Recognition of 3D Emblematic Gestures -- Social Signals -- Types of Help in the Teacher’s Multimodal Behavior -- Honest Signals and Their Contribution to the Automatic Analysis of Personality Traits – A Comparative Study -- Speech Emotion Classification and Public Speaking Skill Assessment -- Dominance Signals in Debates.

It was a great pleasure to organize the First International Workshop on Human Behavior Understanding (HBU), which took place as a satellite workshop to International Conference on Pattern Recognition (ICPR) on August 22, 2010, in Istanbul, Turkey. This workshop arose from the natural marriage of pattern recognitionwiththerapidlyadvancingareaofhumanbehavioranalysis.Ouraim was to gather researchersdealing 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 pattern recognition approaches that involve multiple modalities and those that model actual dynamics of behavior. The contiguity with ICPR, one of the most important events in the p- tern recognition and machine learning communities, is expected to foster cro- pollination with other areas, for example temporal pattern mining or time - ries analysis, which share their important methodological aspects with human behavior understanding. Furthermore, the presence of this workshop at ICPR was meant to attract researchers, in particular PhD students and postd- toral researchers, to work on the questions of human behavior understanding that is likely to play a major role in future technologies (ambient intelligence, human–robot interaction, arti?cial social intelligence, etc.), as witnessed by a number of researche?orts aimed at collecting and annotating large sets of multi sensor data,collected from observingpeople in naturaland often technologically challenging conditions.