The Community for Technology Leaders
Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
ISBN: 978-0-7695-3507-4
pp: 533-536
Poyang lake of Jiangxi province, China, is the biggest wetland of China. It is one of the largest bases of the migrant birds especially in winter. The nature ecosystem of the region has relationship with the birds’ activities, and vice versa. Research of the birds is one of the important ways for knowing the ecosystem. We attempt to set up a system of surveillance and estimation of the bird types and amounts from video. The background of the landscape is the wild field, mainly including lake, grass, and sky. The video camera is the handy one. Because of the wild birds such as the Cygnus’s nature, they are likely settle in a large amount in the lake bay and are far away from the observers. The amount may be over 10,000 that the view of field has to pan slowly in the horizontal to capture all of them. So we have to face up with the problem of the moving background together with the small and crowd objects. In this paper we propose a method based on adaptive filtering and morphological algorithm for moving object detection. It aims at relevant low complex of the computation and also robust for most scenes. Firstly the camera motion is eliminated using motion compensation. The predict frame is estimated from the last frame, and difference image is obtained by filtering of the predicted frame and the current frame. The pixels of the moving objects show high values. The distribution of the difference is modeled as a Gaussian function and a segmentation threshold is calculated adaptively according to the distribution function. Then the segmented moving pixels are detected and dilated to construct approximate parts of objects. At last, motion directions and speeds of the moving parts are computed by matching them of the sequent frames and be used to cluster the parts into objects. The experiment shows the efficiency of this method.
Video, Motion detection, Bird, Optical flow

Y. Yin, Y. Li and B. Xu, "Bird Objects Detection and Tracking on the Wild Field Circumstance," 2009 WRI World Congress on Computer Science and Information Engineering, CSIE(CSIE), Los Angeles, CA, 2009, pp. 533-536.
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