Key Frame Extraction Based on Chaos Theory and Color Information for Video Summarization

Jaeyong JU; Taeyup SONG; Bonhwa KU; Hanseok KO

doi:10.1587/transinf.2015EDL8247

Key Frame Extraction Based on Chaos Theory and Color Information for Video Summarization

Jaeyong JU, Taeyup SONG, Bonhwa KU, Hanseok KO

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Summary :

Key frame based video summarization has emerged as an important task for efficient video data management. This paper proposes a novel technique for key frame extraction based on chaos theory and color information. By applying chaos theory, a large content change between frames becomes more chaos-like and results in a more complex fractal trajectory in phase space. By exploiting the fractality measured in the phase space between frames, it is possible to evaluate inter-frame content changes invariant to effects of fades and illumination change. In addition to this measure, the color histogram-based measure is also used to complement the chaos-based measure which is sensitive to changes of camera /object motion. By comparing the last key frame with the current frame based on the proposed frame difference measure combining these two complementary measures, the key frames are robustly selected even under presence of video fades, changes of illumination, and camera/object motion. The experimental results demonstrate its effectiveness with significant improvement over the conventional method.

Publication: IEICE TRANSACTIONS on Information Vol.E99-D No.6 pp.1698-1701

Publication Date: 2016/06/01

Publicized: 2016/02/23

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2015EDL8247

Type of Manuscript: LETTER

Category: Image Processing and Video Processing

Authors

Jaeyong JU
  Korea University
Taeyup SONG
  Korea Univeristy
Bonhwa KU
  Korea University
Hanseok KO
  Korea University

Keyword

key frame extraction, video summarization, chaos theory, content change

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Jaeyong JU, Taeyup SONG, Bonhwa KU, Hanseok KO, "Key Frame Extraction Based on Chaos Theory and Color Information for Video Summarization" in IEICE TRANSACTIONS on Information, vol. E99-D, no. 6, pp. 1698-1701, June 2016, doi: 10.1587/transinf.2015EDL8247.
Abstract: Key frame based video summarization has emerged as an important task for efficient video data management. This paper proposes a novel technique for key frame extraction based on chaos theory and color information. By applying chaos theory, a large content change between frames becomes more chaos-like and results in a more complex fractal trajectory in phase space. By exploiting the fractality measured in the phase space between frames, it is possible to evaluate inter-frame content changes invariant to effects of fades and illumination change. In addition to this measure, the color histogram-based measure is also used to complement the chaos-based measure which is sensitive to changes of camera /object motion. By comparing the last key frame with the current frame based on the proposed frame difference measure combining these two complementary measures, the key frames are robustly selected even under presence of video fades, changes of illumination, and camera/object motion. The experimental results demonstrate its effectiveness with significant improvement over the conventional method.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2015EDL8247/_p

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@ARTICLE{e99-d_6_1698,
author={Jaeyong JU, Taeyup SONG, Bonhwa KU, Hanseok KO, },
journal={IEICE TRANSACTIONS on Information},
title={Key Frame Extraction Based on Chaos Theory and Color Information for Video Summarization},
year={2016},
volume={E99-D},
number={6},
pages={1698-1701},
abstract={Key frame based video summarization has emerged as an important task for efficient video data management. This paper proposes a novel technique for key frame extraction based on chaos theory and color information. By applying chaos theory, a large content change between frames becomes more chaos-like and results in a more complex fractal trajectory in phase space. By exploiting the fractality measured in the phase space between frames, it is possible to evaluate inter-frame content changes invariant to effects of fades and illumination change. In addition to this measure, the color histogram-based measure is also used to complement the chaos-based measure which is sensitive to changes of camera /object motion. By comparing the last key frame with the current frame based on the proposed frame difference measure combining these two complementary measures, the key frames are robustly selected even under presence of video fades, changes of illumination, and camera/object motion. The experimental results demonstrate its effectiveness with significant improvement over the conventional method.},
keywords={},
doi={10.1587/transinf.2015EDL8247},
ISSN={1745-1361},
month={June},}

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TY - JOUR
TI - Key Frame Extraction Based on Chaos Theory and Color Information for Video Summarization
T2 - IEICE TRANSACTIONS on Information
SP - 1698
EP - 1701
AU - Jaeyong JU
AU - Taeyup SONG
AU - Bonhwa KU
AU - Hanseok KO
PY - 2016
DO - 10.1587/transinf.2015EDL8247
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2016
AB - Key frame based video summarization has emerged as an important task for efficient video data management. This paper proposes a novel technique for key frame extraction based on chaos theory and color information. By applying chaos theory, a large content change between frames becomes more chaos-like and results in a more complex fractal trajectory in phase space. By exploiting the fractality measured in the phase space between frames, it is possible to evaluate inter-frame content changes invariant to effects of fades and illumination change. In addition to this measure, the color histogram-based measure is also used to complement the chaos-based measure which is sensitive to changes of camera /object motion. By comparing the last key frame with the current frame based on the proposed frame difference measure combining these two complementary measures, the key frames are robustly selected even under presence of video fades, changes of illumination, and camera/object motion. The experimental results demonstrate its effectiveness with significant improvement over the conventional method.
ER -