Multi-modal RGB–Depth–Thermal Human Body Segmentation

This work addresses the problem of human body segmentation from multi-modal visual cues as a first stage of automatic human behavior analysis. We propose a novel RGB–depth–thermal dataset along with a multi-modal segmentation baseline. The several modalities are registered using a calibration device...

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Bibliographic Details
Published in:	International journal of computer vision Vol. 118; no. 2; pp. 217 - 239
Main Authors:	Palmero, Cristina, Clapés, Albert, Bahnsen, Chris, Møgelmose, Andreas, Moeslund, Thomas B., Escalera, Sergio
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.06.2016 Springer Springer Nature B.V
Subjects:	Algorithms Artificial Intelligence Calibration Computer Imaging Computer Science Computer vision Data mining Datasets Feature extraction Human acts Human behavior Human body Human subjects Image Processing and Computer Vision Image processing systems Learning Machine learning Mathematical analysis Pattern Recognition Pattern Recognition and Graphics Probabilistic methods Probability theory Registration Segmentation State of the art Studies Support vector machines Vision Vision systems RGB Depth Human body segmentation Thermal
ISSN:	0920-5691, 1573-1405
Online Access:	Get full text
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