DocumentCode :
3224833
Title :
Image basic features indexing techniques for video skimming
Author :
Di Lecce, V. ; Dimauro, G. ; Guerriero, A. ; Impedovo, S. ; Pirlo, G. ; Salzo, A.
Author_Institution :
DEE, Politecnico di Bari, Italy
fYear :
1999
fDate :
1999
Firstpage :
715
Lastpage :
720
Abstract :
In this paper a comparison of the most widespread automatic indexing techniques, suitable in skimmed video generation, and their performances is presented. To evaluate the performances, using the low-level frame features, the signatures are computed, the shots are identified using neural network clustering techniques, in each shot the mean distance between contiguous frames is computed and the shot is resampled according to a related distance value to produce a skimmed video sequence. The most relevant feature proves to be the angular spectrum. Using this feature the mean value of the skimming factor is 2.6 in the used test set
Keywords :
database indexing; feature extraction; image representation; image sampling; image sequences; neural nets; video databases; angular spectrum; automatic indexing; distance value; feature indexing; image basic features; low-level frame features; mean distance; neural network clustering techniques; performance; resampling; shot identification; signature computation; video generation; video skimming; Histograms; Image color analysis; Image retrieval; Indexing; Information retrieval; Layout; Shape; Textiles; Tiles; Video sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Processing, 1999. Proceedings. International Conference on
Conference_Location :
Venice
Print_ISBN :
0-7695-0040-4
Type :
conf
DOI :
10.1109/ICIAP.1999.797679
Filename :
797679
Link To Document :
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