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With this workshop we plan to bring together researchers from different disciplines around signal processing, machine learning, computer vision and robotics with application in HRI/HCI fields, as related to multimodal and multi-sensor processing.

Researchers  are called to present  their latest  advances and discuss  novel  approaches. Emphasis will be  given in new ideas across the interdisciplinary areas mentioned above in the context of multimodality. 

 

The proceedings of the workshop will be included in the EUSIPCO 2017 Conference Proceedings on IEEE Xplore®. 

You may download the Call-for-Papers in pdf.

Important dates are listed here.  

Submission instructions can be found here.

List of topics
The list of topics include (but are not limited to):

  • Gesture recognition 

  • Action and complex activities recognition

  • Deep learning for multimodal recognition

  • Sequential modeling with deep learning

  • Spatiotemporal action localization

  • Sign language analysis and recognition

  • Facial expression modelling and recognition 

  • Human body pose estimation and tracking

  • Hand tracking 

  • 3D Face modelling and analysis 

  • Object detection and tracking for HCI/HRI

  • Vision-based Human Computer/Human Robot Interaction

  • Visual fusion of manual and non-manuals

  • Multimodal emotion recognition

  • Affective computing 

  • Human behaviour analysis,  modeling, and recognition

  • Multi-view subspace learning 

  • Multiview/multimodal invariance learning

  • Audio-visual behaviour analysis

  • Multimodal sensory processing and fusion

  • Multimodal HRI

  • Music and audio in multimodal applications

  • Multimodal HRI for educative applications 

  • Physical human-robot interaction

  • Human-aware interaction control of assistive robots

  • Cognitive robot control architectures

  • Context and intention awareness

  • Corpora, datasets and annotations

  • Human-robot communication in assistive robotics

  • Elderly care mobility assistive robots

  • Assistive applications for children in the autism spectrum

  • Learning for Human-Robot interaction

  • Performance and task monitoring during Human-Robot interaction

  • Time series modeling and classification

MultiLearn Workshop

2017

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