@inproceedings{dd2079584be84c61a7b13b00b647294a,
title = "Supervised spectral embedding for human pose estimation",
abstract = "In exemplar-based approaches for human pose estimation, it is common to extract multiple features to better describe the visual input data. However, simply concatenating multiview features into a long vector has two shortcomings: (1) it suffers from {"}curse of dimensionality{"}; (2) it is not physically meaningful and may be incapable of fully exploiting the complementary properties of multi-view features. To address such problems, in this paper we present a dimension reduction method based on supervised spectral embedding, followed by an ensemble of nearest neighbor regressions in multi-view feature space, to infer 3D human poses from monocular videos. The experiments on HumanEva dataset show the effectiveness of the proposed method.",
keywords = "Human pose estimation, K-NN regression, Spectral embedding",
author = "Yukun Guo and Zhonggui Chen and Jun Yu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015 ; Conference date: 14-06-2015 Through 16-06-2015",
year = "2015",
doi = "10.1007/978-3-319-23989-7\_11",
language = "英语",
isbn = "9783319239873",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "100--109",
editor = "Xiaofei He and Zhi-Hua Zhou and Xinbo Gao and Zhi-Yong Liu and Yanning Zhang and Baochuan Fu and Fuyuan Hu and Zhancheng Zhang",
booktitle = "Intelligence Science and Big Data Engineering",
address = "德国",
}