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Proceedings Paper

A small object detection method based on local maxima and SSD
Author(s): Lei Bo; Tan Hai; Fan Qiang
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Paper Abstract

Small object detection in complex scene is a difficult task in image processing. Normally, small objects in images are also weak objects where the contrast between targets and background is so subtle which makes it difficult to perceive. SSD(Single Shot MultiBox Detector) is one of the object detection method proved to be effective for normal size object detection, otherwise, unable to handle the small target task. A new small object detection method based on SSD is brought up in this paper. At first, a local maxima detector is performed in the image to obtain local maxima points in the image, which would be considered as the center of prior boxes for the subsequent object detection in feature maps of different levels. Secondly, the object extraction would be performed in con2_2 and conv3_3, that assures small objects does not be disappear in high level feature maps. Finally, a method to mark small object is brought up. The proposed method is performed in in several videos, which prove this method is feasible and effective.

Paper Details

Date Published: 18 December 2019
PDF: 7 pages
Proc. SPIE 11342, AOPC 2019: AI in Optics and Photonics, 113420Q (18 December 2019); doi: 10.1117/12.2548076
Show Author Affiliations
Lei Bo, Huazhong Institute of Electro-Optics (China)
Tan Hai, Huazhong Institute of Electro-Optics (China)
Fan Qiang, Huazhong Institute of Electro-Optics (China)

Published in SPIE Proceedings Vol. 11342:
AOPC 2019: AI in Optics and Photonics
John Greivenkamp; Jun Tanida; Yadong Jiang; HaiMei Gong; Jin Lu; Dong Liu, Editor(s)

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