A novel multi-object detection method in complex scene using synthetic aperture imaging
A novel multi-object detection method in complex scene using synthetic aperture imaging
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DOI：
10.1016/j.patcog.2011.10.003
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发表时间：
2012-04
期刊：
影响因子：
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通讯作者：
Zhao Pei;Yanning Zhang;Tao Yang;Xiu-zhong Zhang;Herbert Yang
中科院分区：
文献类型：
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作者：
Zhao Pei;Yanning Zhang;Tao Yang;Xiu-zhong Zhang;Herbert Yang
提出了一种基于多摄像机的多目标检测方法。与传统的多相机对象检测方法不同，我们的方法使用线性相机阵列检测多个对象。该阵列可以流式传输环境的不同视图，并且与头顶环绕配置相比，可以轻松地针对场景进行重新配置。使用所提出的方法，合成的结果不仅可以提供显着闭塞的对象的意见，但也聚焦在目标上的能力，而模糊不感兴趣的对象。我们的方法不需要重建的三维结构的场景，可以容纳动态的背景，是能够检测在任何深度的对象使用一种新的合成孔径成像方法的基础上一个简单的移位变换，并可以看到通过遮挡。实验结果表明，该方法具有良好的性能，可以合成的对象位于任何指定的深度区间，更好的清晰度比使用现有的方法。据我们所知，这是第一次，这种方法使用合成孔径成像已被提出和开发的多目标检测在一个复杂的场景中，在不同的深度有显着的闭塞。
This paper proposes a novel multi-object detection method using multiple cameras. Unlike conventional multi-camera object detection methods, our method detects multiple objects using a linear camera array. The array can stream different views of the environment and can be easily reconfigured for a scene compared with the overhead surround configuration. Using the proposed method, the synthesized results can provide not only views of significantly occluded objects but also the ability of focusing on the target while blurring objects that are not of interest. Our method does not need to reconstruct the 3D structure of the scene, can accommodate dynamic background, is able to detect objects at any depth using a new synthetic aperture imaging method based on a simple shift transformation, and can see through occluders. The experimental results show that the proposed method has a good performance and can synthesize objects located within any designated depth interval with much better clarity than that using an existing method. To our best knowledge, it is the first time that such a method using synthetic aperture imaging has been proposed and developed for multi-object detection in a complex scene with a significant occlusion at different depths.