Name
Abstract | ||
|---|---|---|
We present several algorithms suitable for analysis of broadcast video. First, we show how wavelet analysis of frames of video can be used to detect transitions between shots in a video stream, thereby dividing the stream into segments. Next we describe how each segment can be inserted into a video database using an indexing scheme that involves a wavelet-based "signature." Finally, we show that during a subsequent broadcast of a similar or identical video clip, the segment can be found in the database by quickly searching for the relevant signature. The method is robust against noise and typical variations in the video stream, even global changes in brightness that can fool histogram-based techniques. In the paper, we compare experimentally our shot transition mechanism to a color histogram Implementation, and also evaluate the effectiveness of our database-searching scheme. Our algorithms are very efficient and run in realtime on a desktop computer. We describe how this technology could be employed to construct a "smart VCR" that was capable of alerting the viewer to the beginning of a specific program or identifying commercials and then muting the volume on the TV. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1007/s005300050137 | Multimedia Syst. |
Keywords | Field | DocType |
Key words:Video database – Video indexing – Content-based retrieval – Shot transition – Wavelet transform | Histogram,Computer vision,Video processing,Video capture,Color histogram,Computer science,Video tracking,Artificial intelligence,Data compression,Video denoising,Multimedia,Video compression picture types | Journal |
Volume | Issue | ISSN |
7 | 5 | 0942-4962 |
Citations | PageRank | References |
7 | 0.95 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaodong Wen | 1 | 7 | 1.29 |
| Theodore D. Huffmire | 2 | 7 | 0.95 |
| Helen H. Hu | 3 | 123 | 18.73 |
| Adam Finkelstein | 4 | 4041 | 299.42 |