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3D point cloud video segmentation based on interaction analysis

Author
Lin, X.; Casas, J.; Pardas, M.
Type of activity
Presentation of work at congresses
Name of edition
Second International Workshop on Video Segmentation
Date of publication
2016
Presentation's date
2016-10-10
Book of congress proceedings
Computer Vision – ECCV 2016 Workshops
First page
821
Last page
835
Publisher
Springer
DOI
10.1007/978-3-319-49409-8_67
Project funding
Heterogeneous information and graph signal processing for the Big Data era. Application to high-throughput, remote sensing, multimedia and human computer interfaces
Repository
http://hdl.handle.net/2117/101137 Open in new window
URL
http://link.springer.com/chapter/10.1007/978-3-319-49409-8_67 Open in new window
Abstract
Given the widespread availability of point cloud data from consumer depth sensors, 3D segmentation becomes a promising building block for high level applications such as scene understanding and interaction analysis. It benefits from the richer information contained in actual world 3D data compared to apparent (projected) data in 2D images. This also implies that the classical color segmentation challenges have recently shifted to RGBD data, whereas new emerging challenges are added as 3D informa...
Citation
Lin, X., Casas, J., Pardas, M. 3D point cloud video segmentation based on interaction analysis. A: Workshop on Video Segmentation. "Computer Vision – ECCV 2016 Workshops". Amsterdam: Springer, 2016, p. 821-835.
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

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