In-sequence video duplicate detection with fast point-to-line matching. Liu, B., Li, Z., Wang, M., & Katsaggelos, A. K. In 2010 IEEE International Conference on Image Processing, pages 1037–1040, sep, 2010. IEEE. Paper doi abstract bibtex A computational geometry approach is developed to detect video duplicate with mild transformations. We model the video sequence as a trajectory after scaling and projection. Through interpolation and equal curve length sampling, part of the frame points is selected. A simplified video representation is the line segment set connecting the left neighboring points. For a given query, match distortion is calculated by projecting the query frame points to the line segment set guided by the frame temporal relationship. Experiments demonstrate the effectiveness of the proposed approach. © 2010 IEEE.
@inproceedings{Bo2010,
abstract = {A computational geometry approach is developed to detect video duplicate with mild transformations. We model the video sequence as a trajectory after scaling and projection. Through interpolation and equal curve length sampling, part of the frame points is selected. A simplified video representation is the line segment set connecting the left neighboring points. For a given query, match distortion is calculated by projecting the query frame points to the line segment set guided by the frame temporal relationship. Experiments demonstrate the effectiveness of the proposed approach. {\textcopyright} 2010 IEEE.},
author = {Liu, Bo and Li, Zhu and Wang, Meng and Katsaggelos, A. K.},
booktitle = {2010 IEEE International Conference on Image Processing},
doi = {10.1109/ICIP.2010.5652956},
isbn = {978-1-4244-7992-4},
issn = {15224880},
keywords = {Cubic interpolation,Curve matching,Duplicate detection},
month = {sep},
pages = {1037--1040},
publisher = {IEEE},
title = {{In-sequence video duplicate detection with fast point-to-line matching}},
url = {http://ieeexplore.ieee.org/document/5652956/},
year = {2010}
}
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