Online video synopsis of structured motion
| Autor: | Liangke Gui, Songde Ma, Wei Fu, Hanqing Lu, Jinqiao Wang |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Structure (mathematical logic)
Motion compensation Computer science business.industry Cognitive Neuroscience ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Context (language use) Collision Motion (physics) Computer Science Applications Term (time) Artificial Intelligence Video tracking Computer vision Artificial intelligence business |
| Zdroj: | Neurocomputing. 135:155-162 |
| ISSN: | 0925-2312 |
| Popis: | With the explosive growth of surveillance video data, video synopsis technology is presented for fast browsing a day's worth of video in several minutes. However, for most existing solutions, motion structure in original videos may be destroyed even considering the temporal consistency of related objects. To maintain the important context cues, in this paper, we propose an online motion structure preserved synopsis approach, which can preserve behavior interactions between different objects in the original video while condensing as much content as possible. By measuring sociological proximity of moving objects, we introduce motion structure as a refined term directly added to the problem of energy minimization. A hierarchical fashion is employed to efficiently search an optimal solution for the problem of video synopsis, in which both the spatial collision and the temporal consistency are considered. Experimental results on extensive videos demonstrate the promise of the proposed approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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