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A novel multi-object detection method in complex scene using synthetic aperture imaging

Authors:

Yee-Hong YangAuthors Info & Claims

Pattern Recognition, Volume 45, Issue 4

Pages 1637 - 1658

https://doi.org/10.1016/j.patcog.2011.10.003

Published: 01 April 2012 Publication History

Abstract

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.

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Cited By

Yu LZhang XLiao WYang WXia G(2023)Learning to See Through With EventsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2022.322744845:7(8660-8678)Online publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1109/TPAMI.2022.3227448
Zhang XZhang YYang TYang Y(2017)Synthetic aperture photography using a moving camera-IMU systemPattern Recognition10.1016/j.patcog.2016.07.01962:C(175-188)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1016/j.patcog.2016.07.019
Yang TMa WWang SLi JYu JZhang Y(2016)Kinect based real-time synthetic aperture imaging through occlusionMultimedia Tools and Applications10.1007/s11042-015-2618-175:12(6925-6943)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1007/s11042-015-2618-1
Show More Cited By

A novel multi-object detection method in complex scene using synthetic aperture imaging
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks

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cover image Pattern Recognition

Pattern Recognition Volume 45, Issue 4

April, 2012

585 pages

ISSN:0031-3203

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Copyright © Elsevier Ltd © 2011.

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Elsevier Science Inc.

United States

Publication History

Published: 01 April 2012

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Cited By

Yu LZhang XLiao WYang WXia G(2023)Learning to See Through With EventsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2022.322744845:7(8660-8678)Online publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1109/TPAMI.2022.3227448
Zhang XZhang YYang TYang Y(2017)Synthetic aperture photography using a moving camera-IMU systemPattern Recognition10.1016/j.patcog.2016.07.01962:C(175-188)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1016/j.patcog.2016.07.019
Yang TMa WWang SLi JYu JZhang Y(2016)Kinect based real-time synthetic aperture imaging through occlusionMultimedia Tools and Applications10.1007/s11042-015-2618-175:12(6925-6943)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1007/s11042-015-2618-1
Song ZZhang YYang TZhang X(2012)High-Quality synthetic aperture auto-imaging under occlusionProceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering10.1007/978-3-642-36669-7_50(407-416)Online publication date: 15-Oct-2012
https://dl.acm.org/doi/10.1007/978-3-642-36669-7_50

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