Name
Abstract | ||
|---|---|---|
This paper proposes a new method that combines the intensity and motion information to detect scene changes such as abrupt scene changes and gradual scene changes. Two major features are chosen as the basic dissimilarity measures, and self- and cross-validation mechanisms are employed via a static scene test. We also develop a novel intensity statistics model for detecting gradual scene changes. Experimental results show that the proposed algorithms are effective and outperform the previous approaches |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/76.974682 | IEEE Trans. Circuits Syst. Video Techn. |
Keywords | Field | DocType |
video signal processing,cross-validation mechanism,false alarm rate,major feature,basic dissimilarity measure,motion information,static scene test,scene-change detection algorithm,index terms—abrupt scene changes,abrupt scene change,statistical analysis,intensity statistics model,image segmentation,dissimilarity measures,self-validation mechanism,threshold selection problem,intensity information,robust scene-change detection method,scene change,scene-change detection.,abrupt scene changes,gradual scene change,image sequences,video segmentation,detection rate,novel intensity statistics model,gradual scene changes,video sequence,image motion analysis,robustness,statistics,video compression,statistical model,layout,cross validation,indexing terms | Signal processing,Computer vision,Change detection,Motion detection,Pattern recognition,Computer science,Segmentation,Image segmentation,Scene statistics,Statistical model,Artificial intelligence,Statistical analysis | Journal |
Volume | Issue | ISSN |
11 | 12 | 1051-8215 |
Citations | PageRank | References |
81 | 5.06 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chung-Lin Huang | 1 | 540 | 37.61 |
| Bing-Yao Liao | 2 | 81 | 5.06 |