ML Anthology

Online Learning for Human-Robot Interaction

Bogdan Raducanu, Jordi Vitrià
CVPR 2007
doi:10.1109/CVPR.2007.383438 /cvpr/2007/raducanu2007cvpr-online/

Abstract

This paper presents a novel approach for incremental subspace learning based on an online version of the non-parametric discriminant analysis (NDA). For many real-world applications (like the study of visual processes, for instance) there is impossible to know beforehand the number of total classes or the exact number of instances per class. This motivated us to propose a new algorithm, in which new samples can be added asynchronously, at different time stamps, as soon as they become available. The proposed technique for NDA-eigenspace representation has been applied to the problem of online face recognition for human-robot interaction scenario.

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Cite

Text

Raducanu and Vitrià. "Online Learning for Human-Robot Interaction." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007. doi:10.1109/CVPR.2007.383438

Markdown

[Raducanu and Vitrià. "Online Learning for Human-Robot Interaction." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007.](https://mlanthology.org/cvpr/2007/raducanu2007cvpr-online/) doi:10.1109/CVPR.2007.383438

BibTeX

@inproceedings{raducanu2007cvpr-online,
  title     = {{Online Learning for Human-Robot Interaction}},
  author    = {Raducanu, Bogdan and Vitrià, Jordi},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2007},
  doi       = {10.1109/CVPR.2007.383438},
  url       = {https://mlanthology.org/cvpr/2007/raducanu2007cvpr-online/}
}