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논문 기본 정보

자료유형
학술대회자료
저자정보
Keita Miyaura (Japan Advanced Institute of Science and Technology) Armagan Elibol (Japan Advanced Institute of Science and Technology) Nak Young Chong (Japan Advanced Institute of Science and Technology)
저널정보
제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2022
발행연도
2022.11
수록면
1,161 - 1,166 (6page)

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초록· 키워드

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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.

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Abstract
1. INTRODUCTION
2. PRE-FILTERING STEP FOR OUTLIER REDUCTION METHOD
3. EXPERIMENTAL RESULTS
4. CONCLUSIONS AND FUTUREWORK
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