NDLI: Video similarity measurement approach via dimensionality reduction with distance space and random projection: Application with sports video classification

Content Provider	IEEE Xplore Digital Library
Author	Mutchima, P. Sanguansat, P.
Copyright Year	2010
Description	Author affiliation: Rangsit University, Thailand (Mutchima, P.; Sanguansat, P.)
Abstract	A critical issue of measuring video similarity is most video data are huge files, which vary in terms of length and amount of data, resulting in time-consuming data processing. Therefore, reducing the dimensionality of the data becomes a necessity. This paper proposes the video similarity measurement approach for sports video classification by dimensionality reduction with distance space and random projection (RP). All frames of training videos are extracted by color histogram based method. After that, the clustering technique is performed to provide the centroids of each cluster, called reference vectors. These vectors are used as a set of basis to create new space, called distance space. For any sequence in distance space, the new feature is represented by the frequencies of similar frame comparing with each reference vector. Afterwards, all features of videos are projected onto a low-dimensional subspace using a random projection. Finally, the nearest neighbor (NN) classifier is applied to compare the similarity of the videos between the training videos and the test videos in new space. Accordingly, the proposed approach helps enhance feature dimension reduction, resulting in faster data processing. The experimental results show that this approach is both efficient and effective in sports video similarity measurement.
Starting Page	430
Ending Page	434
File Size	102383
Page Count	5
File Format	PDF
ISBN	9781424470075
e-ISBN	9781424470105
e-ISBN	9781424470099
DOI	10.1109/ISCIT.2010.5664878
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-26
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Distance Space Random Projection Video sequences Reference Vectors Video Similarity Measurement Sports Video Training Histograms Accuracy Image color analysis Video Classification Feature extraction
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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