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