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A Geometrical Key-Frame Selection Method Exploiting Dominant Motion Estimation in Video (2004)
| Venue: | In IEEE International Conference on Content-based Image and Video Retrieval |
| Citations: | 15 - 0 self |
BibTeX
@INPROCEEDINGS{Fauvet04ageometrical,
author = {Brigitte Fauvet and Patrick Bouthemy and Patrick Gros and Fabien Spindler},
title = {A Geometrical Key-Frame Selection Method Exploiting Dominant Motion Estimation in Video},
booktitle = {In IEEE International Conference on Content-based Image and Video Retrieval},
year = {2004},
pages = {419--427}
}
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Abstract
Abstract. We describe an original method for selecting key frames to represent the content of every shot in a video. We aim at spatially sampling in an uniform way the coverage of the scene viewed in each shot. Our method exploits the computation of the dominant image motion (assumed to be due to the camera motion) and mainly relies on geometrical properties related to the incremental contribution of a frame in the considered shot. We also present a refinement of the proposed method to obtain a more accurate representation of the scene, but at the cost of a higher computation time, by considering the iterative minimization of an appropriate energy function. We report experimental results on sports videos and documentaries which demonstrate the accuracy and the efficiency of the proposed approach. 1 Introduction and related work In video indexing and retrieval, representing every segmented shot of the processed video by one appropriate frame, called key-frame, or by a small set of key-frames, is a common useful early processing step. When considering fast video content visualization,
Keyphrases
video content visualization geometrical property incremental contribution uniform way iterative minimization camera motion appropriate frame accurate representation related work common useful early processing step small set experimental result key frame sport video dominant image motion original method appropriate energy function computation time video indexing
