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The vernissage corpus: A conversational Human-Robot-Interaction dataset
TLDR
We introduce a new conversational Human-Robot-Interaction (HRI) dataset with a real-behaving robot inducing interactive behavior with and between humans. Expand
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Who Will Get the Grant?: A Multimodal Corpus for the Analysis of Conversational Behaviours in Group Interviews
TLDR
In the last couple of years more and more multimodal corpora have been created. Expand
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Combining dynamic head pose-gaze mapping with the robot conversational state for attention recognition in human-robot interactions
TLDR
We propose a dynamic Bayesian model for the VFOA recognition from head pose, where we make two main contributions.Inspired from the behavioral models for body, head and gaze dynamics in gaze shifts, we propose novel gaze models that dynamically and more accurately predict the expected head orientation used for looking in a given gaze target direction.Exploiting the robot conversational state as context to reduce recognition ambiguities. Expand
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THE VERNISSAGE CORPUS: A MULTIMODAL HUMAN-ROBOT-INTERACTION DATASET
TLDR
We introduce a new multimodal interaction dataset with extensive annotations in a conversational Human-Robot-Interaction (HRI) scenario. Expand
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Evaluation of Background Subtraction Methods
TLDR
In this paper we evaluate and compare six well-known foreground from background subtraction methods against a standard database. Expand
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Context aware addressee estimation for human robot interaction
TLDR
The paper investigates the problem of addressee recognition -to whom a speaker's utterance is intended- in a setting involving a humanoid robot interacting with multiple persons. Expand
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Recognizing the Visual Focus of Attention for Human Robot Interaction
TLDR
We address the recognition of people's visual focus of attention (VFOA), the discrete version of gaze that indicates who is looking at whom or what. Expand
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Investigating the midline effect for visual focus of attention recognition
TLDR
This paper addresses the recognition of people's visual focus of attention (VFOA), the discrete version of gaze indicating who is looking at whom or what. Expand
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Leveraging the robot dialog state for visual focus of attention recognition
TLDR
We propose a dynamic Bayesian model that accounts for the robot conversational state (speaking status, person he addresses, reference to objects) along with a dynamic head-to-gaze mapping function. Expand
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Leveraging Semi-Supervised Learning for Fairness using Neural Networks
TLDR
In this paper, we propose a semi-supervised algorithm using neural networks benefiting from unlabeled data to mitigate the bias in the training data. Expand
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