Extended Temporal Ordinal Measurement Using Spatially Normalized Mean for Video Copy Detection
| Autor: | June Kim, HeungKyu Lee |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Subtractive color
General Computer Science Property (programming) business.industry Feature extraction Video copy detection Pattern recognition Electronic Optical and Magnetic Materials Level of measurement Distortion Artificial intelligence Electrical and Electronic Engineering Precision and recall business Block (data storage) Mathematics |
| Zdroj: | ETRI Journal. 32:490-492 |
| ISSN: | 1225-6463 |
| DOI: | 10.4218/etrij.10.0209.0485 |
| Popis: | This letter proposes a robust feature extraction method using a spatially normalized mean for temporal ordinal measurement. Before computing a rank matrix from the mean values of nonoverlapped blocks, each block mean is normalized so that it obeys the invariance property against linear additive and subtractive noise effects and is insensitive against multiplied and divided noise effects. Then, the temporal ordinal measures of spatially normalized mean values are computed for the feature matching. The performance of the proposed method showed about 95% accuracy in both precision and recall rates on various distortion environments, which represents the 2.7% higher performance on average compared to the temporal ordinal measurement. |
| Databáze: | OpenAIRE |
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