Novel micro aerial vehicle video segmentation algorithm
Authors: 
R. Girisha, S. MuraliAuthors Info & Claims
Article No.: 27, Pages 1 - 4
Abstract
A camera mounted on a MICro Aerial Vehicle (MICAV) provides an excellent means to monitor large areas of a scene. In this paper, we present a novel approach for detecting motion regions in video sequence observed by a moving MICAV. Foreground object segmentation is done in four levels. In the first level, we use Pearson correlation coefficient (rab) to segment foreground from background. In the second level, we apply, self shadow removal algorithm based on Difference in Mean (Z) method. And in third and fourth stage, any remaining background spurious noise is removed concurrently, first calculating global histogram and then using local histogram based methods using HSI color space. The experiment is conducted on MICAV video and result shows the effectiveness of the proposed technique.
References
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Girisha R and Murali S, "Motion Segmentation from Surveillance Videos using Varied Number of Frames", Proceedings of the International Journal of Recent Trends in Engineering, ISSN 1797-9617, Volume 2, Number 2, November 2009.
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Girisha R and Murali S, "Self Shadow Elimination Algorithm for Surveillance Videos using Inferential Difference in Mean Statistics", International Journal of Computer Applications 1(27):1--8, February 2010.
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Takeshi Takai et al., "Self shadows and cast shadows in estimating illumination distribution", 4th European Conference on Visual Media Production 27-28 Nov. 2007 Page(s):1--10
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Index Terms
- Novel micro aerial vehicle video segmentation algorithm
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March 2011
194 pages
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Published: 25 March 2011
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