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Robust Motion Detection in Real-Life Scenarios.
・ISBN 978-1-4471-4215-7 paper EUR 49.99
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| 著者・編者 | Martinez-Martin, Ester / Pobil, Angel P. del, |
|---|---|
| シリーズ | (SpringerBriefs in Computer Science) |
| 出版社 | (Springer London Ltd, UK) |
| 出版年月 | 2012 |
| ページ数 | 108 pp. |
| 言語 | ENG |
| ニュース番号 | <A05-24850> |
解説
This work proposes a complete sensor-independent visual system that provides robust target motion detection. First, the way sensors obtain images, in terms of resolution distribution and pixel neighbourhood, is studied. This allows a spatial analysis of motion to be carried out. Then, a novel background maintenance approach for robust target motion detection is implemented. Two different situations are considered: a fixed camera observing a constant background where objects are moving; and a still camera observing objects in movement within a dynamic background. This distinction lies on developing a surveillance mechanism without the constraint of observing a scene free of foreground elements for several seconds when a reliable initial background model is obtained, as that situation cannot be guaranteed when a robotic system works in an unknown environment. Other problems are also addressed to successfully deal with changes in illumination, and the distinction between foreground and background elements.