Moving object detection in aerial video based on spatiotemporal saliency

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• 作者：Hao Shen ; Shuxiao Li ; Chengfei Zhu ; Hongxing Chang ; Jinglan Zhang
• 关键词：Aerial video ; Computer vision ; Object detection ; Saliency ; Unmanned aerial vehicles
• 刊名：Chinese Journal of Aeronautics
• 出版年：2013
• 出版时间：October, 2013
• 年：2013
• 卷：26
• 期：5
• 页码：1211-1217
• 全文大小：1596 K

文摘

In this paper, the problem of moving object detection in aerial video is addressed. While motion cues have been extensively exploited in the literature, how to use spatial information is still an open problem. To deal with this issue, we propose a novel hierarchical moving target detection method based on spatiotemporal saliency. Temporal saliency is used to get a coarse segmentation, and spatial saliency is extracted to obtain the object¡¯s appearance details in candidate motion regions. Finally, by combining temporal and spatial saliency information, we can get refined detection results. Additionally, in order to give a full description of the object distribution, spatial saliency is detected in both pixel and region levels based on local contrast. Experiments conducted on the VIVID dataset show that the proposed method is efficient and accurate.