Short-term motion-based object segmentation
| Autor: | Michael Tok, Andreas Krutz, Marina Georgia Arvanitidou, Thomas Sikora |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Motion compensation
business.industry Segmentation-based object categorization Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-space segmentation Image segmentation Thresholding Quarter-pixel motion Motion field Match moving Motion estimation Structure from motion Computer vision Segmentation Artificial intelligence business Block-matching algorithm |
| Zdroj: | ICME |
| DOI: | 10.1109/icme.2011.6011873 |
| Popis: | Motion-based segmentation approaches employ either longterm motion information, which is computationally demanding, or suffer from lack of accuracy when employing short-term information. We present an automatic motion-based object segmentation algorithm for video sequences with moving camera, employing short-term motion information solely. For every frame, two error frames are generated using motion compensation. They are combined and a thresholding segmentation algorithm is applied. Recent advances in the field of global motion estimation enable outlier elimination in the background area, and thus a more precise definition of the foreground is achieved. We propose a simple and effective error frame generation and consider spatial error localization. Thus, we achieve improved performance compared with a previously proposed short-term motion-based method and provide subjective as well as objective evaluation. |
| Databáze: | OpenAIRE |
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