Video Retrieval: An Adaptive Novel Feature Based Approach for Movies

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Author(s)

Viral B. Thakar 1,* Chintan B. Desai 1 S.K. Hadia 1

1. CHARUSAT

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2013.03.04

Received: 7 Nov. 2012 / Revised: 14 Dec. 2012 / Accepted: 24 Jan. 2013 / Published: 8 Mar. 2013

Index Terms

Abrupt transitions, Features reduction, Minimum features based algorithm, Video Retrieval

Abstract

Video Retrieval is a field, where many techniques and methods have been proposed and have claimed to perform reliably on the videos like broadcasting of news & sports events. As a movie contains a large amount of visual information varying in random manner, it requires a highly robust algorithm for automatic shot boundary detection as well as retrieval. In this paper, we described a new adaptive approach for shot boundary detection which is able to detect not only abrupt transitions like hard cuts but also special effects like wipes, fades, and dissolves as well in different movies. To partition a movie video into shots and retrieve many metrics were constructed to measure the similarity among video frames based on all the available video features. However, too many features will reduce the efficiency of the shot boundary detection. Therefore, it is necessary to perform feature reduction for every decision. For this purpose we are following a minimum features based algorithm.

Cite This Paper

Viral B. Thakar, Chintan B. Desai, S.K. Hadia,"Video Retrieval: An Adaptive Novel Feature Based Approach for Movies", IJIGSP, vol.5, no.3, pp.26-35, 2013.DOI: 10.5815/ijigsp.2013.03.04

Reference

[1]http://royal.pingdom.com/2012/01/17/internet-2011-in-numbers/

[2]Seung-Hoon Han, Kuk-Jin Yoon, and In So Kweon, 2000. "A new technique for shot detection and key frames selection in histogram space."12th Workshop on Image Processing and Image Understanding, pp 475-479

[3]Analysis and Verification of Shot Boundary Detection in Video using Block Based χ2 Histogram Method by 1Naimish.Thakar, 2Prof.P.I.Panchal, 3Upesh Patel, 4Ketan Chaudhari, 5Santosh.Sangada in International Journal of Advances in Electronics Engineering

[4]HYBRID APPROACH FOR SHOT BOUNDARY DETECTION FROM UNCOMPRESSED VIDEO STREAM 1Ketan Chaudhari, 2Santosh Sangada, 3Upesh Patel, 4Prof.J.P. Chaudhari, 5Prof.P.I.Panchal in International Journal of Advances in Electronics Engineering

[5]Shot boundary detection via similarity analysis by Matthew Cooper Jonathan Foote, John Adcock, and SandeepCasi FX Palo Alto Laboratory Palo Alto, CA USA http://www.fxpal.com

[6]A. Hanjalic, Shot-boundary detection: unraveled and resolved?, Circuits and Systems for Video Technology, IEEE Transactions on 12 (2) (2002) 90–105.

[7]SVM-based shot boundary detection with a novel feature by kazunorimatsumotomasakinaitokddir&d laboratories, inc. 2-1-15 ohara, fujimino-shi, saitama 356-8502, japan {matsu, hoashi, naito, fsugaya}@kddilabs.jpkeiichirohoashifumiakisugaya

[8]Costas Cotsaces "Video Shot Boundary Detection and Condensed Representation: A Review" Student Member, IEEE, Nikos Nikolaidis, Member, IEEE,andIoannis Pitas, Senior Member, IEEE.

[9]Comparison of Automatic Shot Boundary Detection Algorithms by Rainer Lienhart1, Microcomputer Research Labs, Intel Corporation, Santa Clara, CA 95052-8819 Rainer.Lienhart@intel.com

[10]Advanced and Adaptive Shot Boundary Detection A. Miene, A. Dammeyer, Th. Hermes, and O. Herzog

[11]Comparison of video shot boundary detection techniques John S. Boreczky Lawrence A. Rowe 

[12]A novel shot boundary detection framework Wujieheng, Jinhui Yuan, Huiyi Wang, Fuzong Lin and Bo Zhang

[13]A. Anjulan, N. Canagarajah, Invariant region descriptors for robust shot segmentation, in: Proceedings of the IS&T/ SPIE, 18th Annual Symposium on Electronic Imaging, California, USA, January 2006

[14]D.G. Lowe, Distinctive image features from scale-invariant key points, Internat. J. Comput. Vision 60 (2004) 91–110.