GPU-accelerated abrupt shot boundary detection
| Autor: | Yuan Zhang, Youxian Zheng |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Boundary detection
Computer science business.industry Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering 02 engineering and technology HSL and HSV Instruction set Support vector machine Robustness (computer science) Analytics Histogram Computer Science::Multimedia 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business |
| Zdroj: | ISCIT |
| DOI: | 10.1109/iscit.2016.7751609 |
| Popis: | The detection of abrupt shot boundary is a fundamental task of video analytics and content-based video retrieval. The traditional methods tend to take much time in frame processing. In this paper, a GPU-accelerated abrupt shot boundary detection algorithm is proposed. This algorithm takes into account of both global feature and local feature of the video frames, in which the block HSV histograms and SURF are accelerated on GPU. We also adopt the GPU-accelerated Support Vector Machine (SVM) to identify the abrupt transitions. With the combination of global and local features, the algorithm is more robust against the abrupt camera/object motion and flash lights. Meanwhile, with the GPU acceleration, the proposed method achieves high speed with high accuracy as well. |
| Databáze: | OpenAIRE |
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