Name
Abstract | ||
|---|---|---|
We describe a fuzzy inference approach for detecting and classifying shot transitions in video sequences. Our approach basically extends FAM(Fuzzy Associative Memory) to detect and classify shot transitions, including cuts, fades and dissolves. We consider a set of feature values that characterize differences between two consecutive frames as input fuzzy sets, and the types of shot transitions as output fuzzy sets. An initial implementation runs at approximately 7 frames per second on PC and yields promising results. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1007/3-540-44596-X_5 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
fam-based fuzzy inference,consecutive frame,output fuzzy set,classifying shot transition,feature value,fuzzy inference approach,fuzzy associative memory,shot transition,input fuzzy set,detecting shot transitions,video sequence,initial implementation,frames per second,associative memory,digital image,fuzzy set,fuzzy logic | Fuzzy associative memory,Content-addressable memory,Computer science,Fuzzy set,Digital image,Artificial intelligence,Pattern recognition,Inference,Fuzzy inference,Fuzzy logic,Algorithm,Frame rate,Machine learning | Conference |
Volume | ISSN | ISBN |
2123 | 0302-9743 | 3-540-42359-1 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seok-Woo Jang | 1 | 55 | 12.72 |
| Gye-Young Kim | 2 | 116 | 24.67 |
| Hyung-Il Choi | 3 | 138 | 26.28 |