Rotational multipyramid network with bounding‐box transformation for object detection

International Journal of Intelligent SystemsVolume 36, Issue 9 p. 5307-5338 RESEARCH ARTICLE Rotational multipyramid network with bounding-box transformation for object detection Donggeun Kim, Donggeun Kim orcid.org/0000-0001-9061-6033 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of KoreaSearch for more papers by this authorSan Kim, San Kim orcid.org/0000-0003-3495-7292 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of KoreaSearch for more papers by this authorSiheon Jeong, Siheon Jeong orcid.org/0000-0002-0532-1212 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of KoreaSearch for more papers by this authorJi-Wan Ham, Ji-Wan Ham orcid.org/0000-0003-1096-4404 Department of Intelligent Energy and Industry, Chung-Ang University, Seoul, Dongjak-gu, Republic of KoreaSearch for more papers by this authorSeho Son, Seho Son orcid.org/0000-0003-3565-4971 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of KoreaSearch for more papers by this authorJoonhyeok Moon, Joonhyeok Moon orcid.org/0000-0003-4358-9954 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of KoreaSearch for more papers by this authorKi-Yong Oh, Corresponding Author Ki-Yong Oh [email protected] orcid.org/0000-0003-2895-4749 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of Korea Department of Intelligent Energy and Industry, Chung-Ang University, Seoul, Dongjak-gu, Republic of Korea Correspondence Ki-Yong Oh, Department of Mechanical Engineering, Hanyang University, 222 Wangsimni-ri, Seongdong-gu, Seoul, 04763, Republic of Korea. Email: [email protected]Search for more papers by this author Donggeun Kim, Donggeun Kim orcid.org/0000-0001-9061-6033 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of KoreaSearch for more papers by this authorSan Kim, San Kim orcid.org/0000-0003-3495-7292 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of KoreaSearch for more papers by this authorSiheon Jeong, Siheon Jeong orcid.org/0000-0002-0532-1212 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of KoreaSearch for more papers by this authorJi-Wan Ham, Ji-Wan Ham orcid.org/0000-0003-1096-4404 Department of Intelligent Energy and Industry, Chung-Ang University, Seoul, Dongjak-gu, Republic of KoreaSearch for more papers by this authorSeho Son, Seho Son orcid.org/0000-0003-3565-4971 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of KoreaSearch for more papers by this authorJoonhyeok Moon, Joonhyeok Moon orcid.org/0000-0003-4358-9954 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of KoreaSearch for more papers by this authorKi-Yong Oh, Corresponding Author Ki-Yong Oh [email protected] orcid.org/0000-0003-2895-4749 Department of Mechanical Engineering, Hanyang University, 22 Wangsimni-ri, Seongdong-gu, Seoul, Republic of Korea Department of Intelligent Energy and Industry, Chung-Ang University, Seoul, Dongjak-gu, Republic of Korea Correspondence Ki-Yong Oh, Department of Mechanical Engineering, Hanyang University, 222 Wangsimni-ri, Seongdong-gu, Seoul, 04763, Republic of Korea. Email: [email protected]Search for more papers by this author First published: 29 May 2021 https://doi.org/10.1002/int.22513Citations: 6Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract The study proposes a rotational multipyramid network (RoMP Net) with bounding-box transformation for object detection. The RoMP Net is a single-stage object detection neural network featuring three characteristics. First, the network uses a rotational bounding box to minimize the effect of background images when extracting features of objects. Bounding-box transformation was proposed to compensate for the limitation of the rotational bounding boxes, which have relatively low prediction accuracy for objects with a high aspect ratio. Second, the RoMP Net introduces a multi-scale and multi-level feature pyramid network to extract distinct and semantic features efficiently. This network architecture ensures high prediction accuracy and robustness regardless of the size and complexity of objects. Third, hyperparameters in the bounding boxes are automatically determined through an unsupervised clustering method. This optimization method is also critical in improving accuracy. The performance of the proposed network and preprocessing methods are validated through image-sets comprising critical components in power transmission facilities, which have a variety of sizes and aspect ratios. This case study demonstrates the effectiveness and robustness of the three key characteristics in the RoMP Net. Furthermore, the RoMP Net outperforms other state-of-the-art deep neural networks in prediction accuracy and robustness for object detection. Specifically, the mean average precision of the RoMP Net in the validation image-sets shows that it has the highest prediction accuracy, whereas its values in the test image-sets confirm the network's robustness. The fast yet accurate RoMP Net will expand the range of object detection through deep neural networks. Citing Literature Volume36, Issue9September 2021Pages 5307-5338 RelatedInformation