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@TECHREPORT{Jayagopi_Idiap-RR-33-2012,
                      author = {Jayagopi, Dinesh Babu and Sheikhi, Samira and Klotz, David and Wienke, Johannes and Odobez, Jean-Marc and Wrede, Sebastian and Khalidov, Vasil and Nguyen, Laurent Son and Wrede, Britta and Gatica-Perez, Daniel},
                    projects = {Idiap, HUMAVIPS},
                       month = {12},
                       title = {The Vernissage Corpus: A Multimodal Human-Robot-Interaction Dataset},
                        type = {Idiap-RR},
                      number = {Idiap-RR-33-2012},
                        year = {2012},
                 institution = {Idiap},
                    abstract = {We introduce a new multimodal interaction dataset with extensive annotations
in a conversational Human-Robot-Interaction (HRI) scenario. It has been recorded and 
annotated to benchmark many relevant perceptual tasks, towards 
enabling a robot to converse with multiple humans, such as   
speaker localization, key word spotting, speech recognition in audio domain;
tracking, pose estimation, nodding, visual focus of attention estimation in visual
domain; and an audio-visual task such as addressee detection. 
Some of the above mentioned tasks could benefit from information sensed from several modalities and recorded states of the robot. 
As compared to recordings done with a static camera, this corpus involves the head-movement of a humanoid 
robot (due to gaze change, nodding), 
making it challenging for tracking. Also, the significant background 
noise present in a real HRI setting makes tasks in the auditory domain more challenging. From the interaction point of view, our scenario, 
where the robot explains paintings in a room and then quizzes the participants, allows to analyze the 
quality of the interaction and the behavior of the human interaction partners.},
                         pdf = {https://publications.idiap.ch/attachments/reports/2012/Jayagopi_Idiap-RR-33-2012.pdf}
}