@inproceedings{09199674a78f4096a23edf72586e46cb,
title = "Heterogeneous discriminant analysis for cross-view action recognition",
abstract = "We propose an approach of cross-view action recognition, in which the samples from different views are represented by heterogeneous features with different dimensions. Inspired by linear discriminant analysis (LDA), we introduce a discriminative common feature space to bridge the source and target views. Two different projection matrices are learned to respectively map the data from two different views into the common space by simultaneously maximizing the similarity of intra-class samples, minimizing the similarity of inter-class samples, and reducing the mismatch between data distributions of two views. Our method is neither restricted to the corresponding action instances in the two views nor restricted to a specific type of feature. We evaluate our approach on the IXMAS multi-view dataset and the experimental results demonstrate its effectiveness.",
keywords = "Cross-view action recognition, Discriminant analysis, Heterogeneous domain adaption, Transfer learning",
author = "Wanchen Sui and Xinxiao Wu and Yang Feng and Wei Liang and Yunde Jia",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 22nd International Conference on Neural Information Processing, ICONIP 2015 ; Conference date: 09-11-2015 Through 12-11-2015",
year = "2015",
doi = "10.1007/978-3-319-26561-2_67",
language = "English",
isbn = "9783319265605",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "566--573",
editor = "Sabri Arik and Tingwen Huang and Lai, {Weng Kin} and Qingshan Liu",
booktitle = "Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings",
address = "Germany",
}