Abrupt Scene Change Detection

Authors: Priyadarshinee Adhikari, Neeta Gargote, Jyothi Digge, B.G. Hogade

Abstract:

A number of automated shot-change detection methods for indexing a video sequence to facilitate browsing and retrieval have been proposed in recent years. This paper emphasizes on the simulation of video shot boundary detection using one of the methods of the color histogram wherein scaling of the histogram metrics is an added feature. The difference between the histograms of two consecutive frames is evaluated resulting in the metrics. Further scaling of the metrics is performed to avoid ambiguity and to enable the choice of apt threshold for any type of videos which involves minor error due to flashlight, camera motion, etc. Two sample videos are used here with resolution of 352 X 240 pixels using color histogram approach in the uncompressed media. An attempt is made for the retrieval of color video. The simulation is performed for the abrupt change in video which yields 90% recall and precision value.

Keywords: Abrupt change, color histogram, ground-truthing, precision, recall, scaling, threshold.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1072533

References:

[1] Gargi, U., Kasturi, R., Strayer, S.H.: Performance Characterization of Video-Shot-Change Detection Methods. IEEE transaction on circuits and systems for video technology 10(1) (2000).
[2] Gonzalez; Digital Image Processing 2/E. Prentice-Hall, Englewood Cliffs (2002).
[3] Rainer Lienhart: Comparison of Automatic Shot Boundary detection Algorithms.
[4] C.F.Lam and M.C.Lee: Video Segmentation using Color Difference Histogram.
[5] Frank Hopfgartner : Interactive Video Retrieval University of Glasgow September 15, 2006.
[6] Nagasaka, A., Tanaka, Y.: Automatic video indexingand full - video search for Object appearances. In: Visual Database Systems II, pp. 113- 127. Elsevier,Amsterdam(1995).
[7] Wei Jyh Heng and King N. Ngan: Integrated Shot Boundary Detection using Object-based Technique.