Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction, 2015
Third IAPR TC3 Workshop, MPRSS 2014, Stockholm, Sweden, August 24, 2014, Revised Selected Papers

Lecture Notes in Artificial Intelligence Series

Coordinators: Schwenker Friedhelm, Scherer Stefan, Morency Louis-Philippe

Language: English

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145 p. · 15.5x23.5 cm · Paperback
This book constitutes the thoroughly refereed post-workshop proceedings of the Third IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2014, held in Stockholm, Sweden, in August 2014, as a satellite event of the International Conference on Pattern Recognition, ICPR 2014. The 14 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.
Automatic Image Collection of Objects with Similar Function by Learning Human Grasping Forms.- Client Specific Image Gradient Orientation for Unimodal and Multimodal Face Representation.- Multiple-Manifolds Discriminant Analysis for Facial Expression Recognition from Local Patches Set.- Monte Carlo Based Importance Estimation of Localized Feature Descriptors for the Recognition of Facial Expressions.- Noisy Speech Recognition Based on Combined Audio-Visual Classifiers.- Complementary Gaussian Mixture Models for Multimodal Speech Recognition.- Fusion of Text and Audio Semantic Representations Through CCA.- uulmMAD – A Human Action Recognition Dataset for Ground-Truth Evaluation and Investigation of View Invariances.- A Real Time Gesture Recognition System for Human Computer Interaction.- A SIFT-Based Feature Level Fusion of Iris and Ear Biometrics.- Audio-Visual User Identification in HCI Scenarios.- Towards an Adaptive Brain-Computer Interface – An Error Potential Approach.- Online Smart Face Morphing Engine with Prior Constraints and Local Geometry Preservation.- Exploring Alternate Modalities for Tag Recommendation.

Includes supplementary material: sn.pub/extras