DocumentCode
1673175
Title
A system for reliable dissolve detection in videos
Author
Lienhart, Rainer ; Zaccarin, A.
Author_Institution
Microprocessor Res. Labs., Intel Corp., Santa Clara, CA, USA
Volume
3
fYear
2001
fDate
6/23/1905 12:00:00 AM
Firstpage
406
Abstract
Automatic shot boundary detection has been an active research area for nearly a decade and has led to high performance detection algorithms for hard cuts, fades and wipes. Reliable dissolve detection, however, is still an unsolved problem. We present the first robust and reliable dissolve detection system. A detection rate of 75% was achieved while reducing the false alarm rate to an acceptable level of 16% on a test video set for which so far the best reported detection and false alarm rate had been 66% and 59%, respectively. In addition, a dissolve´s temporal extent is estimated, too. The core ideas of our novel approach are firstly the creation of a dissolve synthesizer capable of creating in principle an infinite number of dissolve examples of any duration from a video database of raw video footage allowing us to use an advanced machine learning algorithm such as neural networks and support vector machines which require large training sets, secondly, two simple features capturing the characteristics of dissolves, thirdly, a fully temporal multi-resolution search based on a fixed position and fixed-scale transition/special effect detector enabling us to determine also the true duration of detected dissolves, and finally, a post processing step which uses global motion estimation to further reduce the number of falsely detected dissolves
Keywords
image resolution; image sequences; learning (artificial intelligence); learning automata; motion estimation; neural nets; video databases; video signal processing; automatic shot boundary detection; detection rate; dissolve synthesizer; fades; false alarm rate reduction; fixed position transition/special effect detector; fixed-scale transition/special effect detector; global motion estimation; hard cuts; machine learning algorithm; neural networks; performance detection algorithms; post processing; reliable dissolve detection; robust dissolve detection system; support vector machines; temporal multi-resolution search; test video set; training sets; video database; video footage; video sequences; wipes; Detection algorithms; Gunshot detection systems; Machine learning algorithms; Motion detection; Neural networks; Robustness; Spatial databases; Synthesizers; Testing; Videos;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location
Thessaloniki
Print_ISBN
0-7803-6725-1
Type
conf
DOI
10.1109/ICIP.2001.958137
Filename
958137
Link To Document