Key Frame Extraction Algorithm for Video Images Based on Correlation Coefficient of Overlap Regions

LU Xiaoping; LU Yao; JIAO Jinlong; TONG Xiaohua; ZHANG Jixian

doi:10.13203/j.whugis20170038

Volume 44 Issue 2

Feb. 2019

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Geomatics and Information Science of Wuhan University > 2019 > 44(2): 260-267. > DOI: 10.13203/j.whugis20170038

LU Xiaoping, LU Yao, JIAO Jinlong, TONG Xiaohua, ZHANG Jixian. Key Frame Extraction Algorithm for Video Images Based on Correlation Coefficient of Overlap Regions[J]. Geomatics and Information Science of Wuhan University, 2019, 44(2): 260-267. DOI: 10.13203/j.whugis20170038

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Key Frame Extraction Algorithm for Video Images Based on Correlation Coefficient of Overlap Regions

LU Xiaoping^1,,
LU Yao^{2, 3, ,},
JIAO Jinlong^{1, 4},
TONG Xiaohua²,
ZHANG Jixian³

1.
Key Laboratory of Mine Spatial Information Technologies of National Administration of Surveying, Mapping and Geoinformation, Henan Polytechnic University, Jiaozuo 454003, China
2.
School of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China
3.
National Quality Inspection and Testing Center for Surveying and Mapping Products, Beijing 100830, China
4.
Institute of Remote Sensing and Surveying and Mapping Henan, Zhengzhou 450003, China

Funds:

The National Key Research and Development Program 2016YFC0803103

the Key Laboratory for Aerial Remote Sensing Technology of NASG 2016B12

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Author Bio:
LU Xiaoping, PhD, professor, specializes in photogrammetry and remote sensing.E-mail: hpuluxp@163.com
Corresponding author:
LU Yao, PhD candidate, engineer, E-mail: 156291029@qq.com
Received Date: April 10, 2018
Published Date: February 04, 2019

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Abstract

Abstract

This paper presents an effective algorithm to extract key frames from video images based on the correlation coefficients derived from the overlapping regions of adjacent images. Firstly, the polynomial model is employed to fit the change trend of correlation coefficients. Secondly, the positions of key frames are located and extracted rapidly and correctly via the high correlation of overlapping regions of adjacent key frame images. Finally, the time-effectiveness of extracting key frames based on the degree of overlap is tested in a stance. The result shows that the proposed algorithm takes only near 1/4 of time consumed by single computing of the degree of overlap, with an accuracy up to 88% and it can achieve higher accuracy for extracting key frames with different requires of degree of overlap between video images. The panchromatic image generated from the mosaic of extracted key video frames shows no apparent missing of scenes, and the new algorithm demonstrates high reliability and transferability.
- video stream data,
- key frame,
- polynomial fitting,
- degree of overlap,
- correlation coefficient

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References (18)

References

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