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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/18172
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| タイトル: | Performance Enhancement Step for Motion Estimation via Feature-based Image Matching |
| 著者: | Miyaura, Keita
ELIBOL, Armagan
Nak-Young, Chong |
| キーワード: | image matching
motion estimation
outlier rejection |
| 発行日: | 2022-11 |
| 出版者: | Institute of Control, Robotics and Systems (ICROS) |
| 誌名: | 2022 22nd International Conference on Control, Automation and Systems (ICCAS) |
| 開始ページ: | 1161 |
| 終了ページ: | 1166 |
| DOI: | 10.23919/ICCAS55662.2022.10003731 |
| 抄録: | Most of the complicated and sophisticated tasks in visual robotics applications usually build upon the image matching step as matching images of the same scene can provide important information (e.g., camera motion). Image matching is generally done via extracting and matching some distinctive points via their feature vectors. This procedure generates some mismatched points due to imperfections. Mismatched points are called outliers and identified via probabilistic methods. Since the probabilistic methods work iteratively, they generally occupy a large portion of the computational cost of the whole image matching pipeline. In this paper, we present a simple yet efficient algorithm that is employed for eliminating the outliers aiming at reducing the total number of iterations needed in the probabilistic methods. Our method is motivated by the common way of visualizing the established matches among images. We tile images together and search for parallel lines connecting correspondences. We present extensive computational and comparative experiments using both simulated data involving along with real images and using a real dataset. |
| Rights: | This is the author's version of the work. Copyright (C)ICROS. 2022 22nd International Conference on Control, Automation and Systems (ICCAS 2022), 2022, pp.1161-1166. DOI:10.23919/ICCAS55662.2022.10003731. Personal use of this material is permitted.This material is posted here with permission of Institute of Control, Robotics and Systems (ICROS). |
| URI: | http://hdl.handle.net/10119/18172 |
| 資料タイプ: | author |
| 出現コレクション: | b11-1. 会議発表論文・発表資料 (Conference Papers)
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このアイテムのファイル:
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| MotEst_ICCAS2022.pdf | | 1661Kb | Adobe PDF | 見る/開く |
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