Locally Embedded Linear Subspaces for Efficient Video Indexing and Retrieval. Li, Z., Gao, L., & Katsaggelos, A. In 2006 IEEE International Conference on Multimedia and Expo, volume 2006, pages 1765–1768, jul, 2006. IEEE. ![Locally Embedded Linear Subspaces for Efficient Video Indexing and Retrieval [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Efficient indexing is a key in content-based video retrieval solutions. In this paper we represent video sequences as traces via scaling and linear transformation of the frame luminance field. Then an appropriate lower dimensional subspace is identified for video trace indexing. We also develop a trace geometry matching algorithm for retrieval based on average projection distance with a locally embedded distance metric. Simulation results demonstrated the high accuracy and very fast retrieval speed for the proposed solution. © 2006 IEEE.
@inproceedings{Zhu2006,
abstract = {Efficient indexing is a key in content-based video retrieval solutions. In this paper we represent video sequences as traces via scaling and linear transformation of the frame luminance field. Then an appropriate lower dimensional subspace is identified for video trace indexing. We also develop a trace geometry matching algorithm for retrieval based on average projection distance with a locally embedded distance metric. Simulation results demonstrated the high accuracy and very fast retrieval speed for the proposed solution. {\textcopyright} 2006 IEEE.},
author = {Li, Zhu and Gao, Li and Katsaggelos, Aggelos},
booktitle = {2006 IEEE International Conference on Multimedia and Expo},
doi = {10.1109/ICME.2006.262893},
isbn = {1-4244-0366-7},
keywords = {Component analysis,High dimensional indexing,Manifold learning,Video retrieval},
month = {jul},
pages = {1765--1768},
publisher = {IEEE},
title = {{Locally Embedded Linear Subspaces for Efficient Video Indexing and Retrieval}},
url = {http://ieeexplore.ieee.org/document/4036962/},
volume = {2006},
year = {2006}
}
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