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Publication Type : Book Chapter
Publisher : Lecture Notes in Computational Vision and Biomechanics
Source : Lecture Notes in Computational Vision and Biomechanics, Book Chapter-2019, Springer Netherlands, Volume 30, p.955-964 (2019)
Campus : Coimbatore
School : School of Engineering
Center : Amrita Innovation & Research
Department : Computer Science
Verified : Yes
Year : 2019
Abstract : Locality Sensitive Hashing (LSH) is an approach which is extensively used for comparing document similarity. In our work, this technique is incorporated in a video environment for finding dissimilarity between the frames in the video so as to detect motion. This has been implemented for a single point camera archiving, wherein the images are converted into pixel file using a rasterization procedure. Pixels are then tokenized and hashed using minhashing procedure which employs a randomized algorithm to quickly estimate the Jaccard similarity. LSH finds the dissimilarity among the frames in the video by breaking the minhashes into a series of band comprising of rows. The proposed procedure is implemented on multiple datasets, and from the experimental analysis, we infer that it is capable of isolating the motions in a video file. Notes: cited By 0
Cite this Research Publication : M. Srenithi and Dr. (Col.) Kumar P. N., “Motion Detection Algorithm for Surveillance Videos”, in Lecture Notes in Computational Vision and Biomechanics, Book Chapter-2019, vol. 30, Springer Netherlands, 2019, pp. 955-964.