Fisher information embedding for video indexing and retrieval

Xu Chen; Alfred O. Hero

doi:10.1117/12.874036

7 February 2011 Fisher information embedding for video indexing and retrieval

Xu Chen, Alfred O. Hero

Author Affiliations +

Proceedings Volume 7873, Computational Imaging IX; 78730A (2011) https://doi.org/10.1117/12.874036
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

In this paper, we present a novel information embedding based approach for video indexing and retrieval. The high dimensionality for video sequences still poses a major challenge of video indexing and retrieval. Different from the traditional dimensionality reduction techniques such as Principal Component Analysis (PCA), we embed the video data into a low dimensional statistical manifold obtained by applying manifold learning techniques to the information geometry of video feature probability distributions (PDF). We estimate the PDF of the video features using histogram estimation and Gaussian mixture models (GMM), respectively. By calculating the similarities between the embedded trajectories, we demonstrate that the proposed approach outperforms traditional approaches to video indexing and retrieval with real world data.

Citation Download Citation

Xu Chen and Alfred O. Hero "Fisher information embedding for video indexing and retrieval", Proc. SPIE 7873, Computational Imaging IX, 78730A (7 February 2011); https://doi.org/10.1117/12.874036

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