Robust Video Retrieval with Luminance Field Trace Indexing and Geometry Matching. Gao, L., Li, Z., & Katsaggelos, A. K. In 2007 International Workshop on Content-Based Multimedia Indexing, pages 99–105, jun, 2007. IEEE. ![Robust Video Retrieval with Luminance Field Trace Indexing and Geometry Matching [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Efficient indexing and robust retrieval are key features for an effective video retrieval system. In this paper we represent video sequences as traces in an appropriate low dimensional space via luminance field scaling and PCA projection, and introduce a combination of top-down and bottom-up strategies for indexing. Various means of introducing distortions in query clips are considered and several heuristics are developed to achieve robustness in retrieval performance. Simulation results demonstrate the effectiveness of the proposed solutions. © 2007 IEEE.
@inproceedings{Li2007,
abstract = {Efficient indexing and robust retrieval are key features for an effective video retrieval system. In this paper we represent video sequences as traces in an appropriate low dimensional space via luminance field scaling and PCA projection, and introduce a combination of top-down and bottom-up strategies for indexing. Various means of introducing distortions in query clips are considered and several heuristics are developed to achieve robustness in retrieval performance. Simulation results demonstrate the effectiveness of the proposed solutions. {\textcopyright} 2007 IEEE.},
author = {Gao, Li and Li, Zhu and Katsaggelos, Aggelos K.},
booktitle = {2007 International Workshop on Content-Based Multimedia Indexing},
doi = {10.1109/CBMI.2007.385398},
isbn = {1-4244-1010-X},
month = {jun},
pages = {99--105},
publisher = {IEEE},
title = {{Robust Video Retrieval with Luminance Field Trace Indexing and Geometry Matching}},
url = {http://ieeexplore.ieee.org/document/4275061/},
year = {2007}
}
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