Robust video retrieval with luminance field trace indexing and geometry matching

Li Gao; Zhu Li; Aggelos K Katsaggelos

doi:10.1109/CBMI.2007.385398

Robust video retrieval with luminance field trace indexing and geometry matching

Li Gao^*, Zhu Li, Aggelos K Katsaggelos

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English (US)
Title of host publication	CBMI'2007 - 2007 International Workshop on Content-Based Multimedia Indexing, Proceedings
Pages	99-105
Number of pages	7
DOIs	https://doi.org/10.1109/CBMI.2007.385398
State	Published - Dec 1 2007
Event	CBMI'2007 - 2007 International Workshop on Content-Based Multimedia Indexing - Bordeaux, France Duration: Jun 25 2007 → Jun 27 2007

Other

Other	CBMI'2007 - 2007 International Workshop on Content-Based Multimedia Indexing
Country	France
City	Bordeaux
Period	6/25/07 → 6/27/07

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Information Systems
Information Systems and Management

Access to Document

10.1109/CBMI.2007.385398

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Cite this

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title = "Robust video retrieval with luminance field trace indexing and geometry matching",

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.",

author = "Li Gao and Zhu Li and Katsaggelos, {Aggelos K}",

year = "2007",

month = dec,

day = "1",

doi = "10.1109/CBMI.2007.385398",

language = "English (US)",

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booktitle = "CBMI'2007 - 2007 International Workshop on Content-Based Multimedia Indexing, Proceedings",

note = "CBMI'2007 - 2007 International Workshop on Content-Based Multimedia Indexing ; Conference date: 25-06-2007 Through 27-06-2007",

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Gao, L, Li, Z & Katsaggelos, AK 2007, Robust video retrieval with luminance field trace indexing and geometry matching. in CBMI'2007 - 2007 International Workshop on Content-Based Multimedia Indexing, Proceedings., 4275061, pp. 99-105, CBMI'2007 - 2007 International Workshop on Content-Based Multimedia Indexing, Bordeaux, France, 6/25/07. https://doi.org/10.1109/CBMI.2007.385398

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N2 - 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.

AB - 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.

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