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.
[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.
[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.
@article{"International Journal of Electrical, Electronic and Communication Sciences:58385", author = "Priyadarshinee Adhikari and Neeta Gargote and Jyothi Digge and B.G. Hogade", title = "Abrupt Scene Change Detection", 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.", volume = "2", number = "6", pages = "1174-6", }