| Presentation | 2022-02-22 A Study on Object Detection in Omnidirectional Images Using Deep Learning Yasuyuki Ishida, Toshio Ito, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | A minimum sensor configuration is desired for a popular automatic vehicle. In this study, an omnidirectional camera with a wide viewing angle is used for object detection to recognize the driving environment. Since an omnidirectional camera has a different appearance from that of a normal monocular camera, geometric transformation is used to perform deep learning. However, the image is segmented at both ends of the object. In this study, we consider the image to be repeated and set annotations to detect objects that are segmented. In addition, since both ends of the omnidirectional image are far away from each other, it is difficult to extract features only by convolutional neural network, so Self Attention is added to the backbone. The accuracy of the network with Self Attention was measured by mAP, and the maximum mAP of the network with Self Attention was 66.5%, which made it possible to detect segmented objects. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Deep Learning / Omnidirectional camera / Object detection / Road environmental recognition |
| Paper # | ITS2021-57,IE2021-66 |
| Date of Issue | 2022-02-14 (ITS, IE) |
| Conference Information | |
| Committee | IE / ITS / ITE-AIT / ITE-ME / ITE-MMS |
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| Conference Date | 2022/2/21(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Image Processing, etc. |
| Chair | Kazuya Kodama(NII) / Masahiro Fujii(Utsunomiya Univ.) / Hisaki Nate(Tokyo Polytechnic Univ.) / Hiroyuki Arai(Nippon Inst. of Tech.) / Kenji Machida(NHK) |
| Vice Chair | Hiroyuki Bandoh(NTT) / Toshihiko Yamazaki(Univ. of Tokyo) / Kohei Ohno(Meiji Univ.) / Naohisa Hashimoto(AIST) / / Shogo Muramatsu(Niigata Univ.) |
| Secretary | Hiroyuki Bandoh(KDDI Research) / Toshihiko Yamazaki(Nagoya Inst. of Tech.) / Kohei Ohno(Akita Prefectural Univ.) / Naohisa Hashimoto(NIT, Tsuruoka College) / / Shogo Muramatsu(NHK) / (Hokkaido Univ.) |
| Assistant | Shunsuke Iwamura(NHK) / Shinobu Kudo(NTT) / Msataka Imao(Mitsubishi Electric) / Kenshi Saho(Toyama Prefectural Univ.) / Keiji Jimi(Gunma Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Image Engineering / Technical Committee on Intelligent Transport Systems Technology / Technical Group on Artistic Image Technology / Technical Group on Media Engineering / Technical Group on Multi-media Storage |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study on Object Detection in Omnidirectional Images Using Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | Deep Learning |
| Keyword(2) | Omnidirectional camera |
| Keyword(3) | Object detection |
| Keyword(4) | Road environmental recognition |
| 1st Author's Name | Yasuyuki Ishida |
| 1st Author's Affiliation | Shibaura Institute of Technology(SIT) |
| 2nd Author's Name | Toshio Ito |
| 2nd Author's Affiliation | Shibaura Institute of Technology(SIT) |
| Date | 2022-02-22 |
| Paper # | ITS2021-57,IE2021-66 |
| Volume (vol) | vol.121 |
| Number (no) | ITS-373,IE-374 |
| Page | pp.pp.190-195(ITS), pp.190-195(IE), |
| #Pages | 6 |
| Date of Issue | 2022-02-14 (ITS, IE) |