the proceedings contain 13 papers. the special focus in this conference is on Multimodal patternrecognition of Social Signals in Human-Computer-Interaction. the topics include: Bimodal recognition of Cognitive Load B...
ISBN:
(纸本)9783319592589
the proceedings contain 13 papers. the special focus in this conference is on Multimodal patternrecognition of Social Signals in Human-Computer-Interaction. the topics include: Bimodal recognition of Cognitive Load Based on Speech and Physiological Changes;Human Mobility-pattern Discovery and Next-Place Prediction from GPS Data;Fusion Architectures for Multimodal Cognitive Load recognition;Performance Analysis of Gesture recognition Classifiers for Building a Human Robot Interface;On Automatic Question Answering Using Efficient Primal-Dual Models;Hierarchical Bayesian Multiple Kernel Learning Based Feature Fusion for Action recognition;Audio Visual Speech recognition Using Deep Recurrent Neural Networks;Audio-Visual recognition of Pain Intensity;the SenseEmotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Painand Emotion-recognition System;Photometric Stereo for 3D Face Reconstruction Using Non Linear Illumination Models and Recursively Measured Action Units.
In this paper we describe a novel HMM-based system for off-line handwriting recognition. We adapt successful techniques from the domains of large vocabulary speech recognition and image object recognition: moment-base...
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In this paper we describe a novel HMM-based system for off-line handwriting recognition. We adapt successful techniques from the domains of large vocabulary speech recognition and image object recognition: moment-based image normalization, writer adaptation, discriminative feature extraction and training, and open-vocabulary recognition. We evaluate those methods and examine their cumulative effect on the recognition performance. the final system outperforms current state-of-the-art approaches on two standard evaluation corpora for English and French handwriting.
this paper presents a robust approach based on evolutionary agents for projective reconstruction in the presence of missing data and unknown depths. Agents denote possible submatrices for rank constraints, and carry o...
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ISBN:
(纸本)0769525210
this paper presents a robust approach based on evolutionary agents for projective reconstruction in the presence of missing data and unknown depths. Agents denote possible submatrices for rank constraints, and carry out some evolutionary behavior to exploit a vast solution space. Our approach combines the benefits of excellent searching ability of evolutionary agents for getting a good solution, with a proper treatment Of missing information with linear fitting. Experimental results demonstrate better performance of our approach than other typical methods in terms of accuracy and robustness to noise and missing data.
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