[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9708/jksci.2022.27.07.049

DB-Based Feature Matching and RANSAC-Based Multiplane Method for Obstacle Detection System in AR

Kim, Jong-Hyun (School of Software Application, Kangnam University)

Publication Information

Journal of the Korea Society of Computer and Information / v.27, no.7, 2022 , pp. 49-55 More about this Journal

Abstract

In this paper, we propose an obstacle detection method that can operate robustly even in external environmental factors such as weather. In particular, we propose an obstacle detection system that can accurately inform dangerous situations in AR through DB-based feature matching and RANSAC-based multiplane method. Since the approach to detecting obstacles based on images obtained by RGB cameras relies on images, the feature detection according to lighting is inaccurate, and it becomes difficult to detect obstacles because they are affected by lighting, natural light, or weather. In addition, it causes a large error in detecting obstacles on a number of planes generated due to complex terrain. To alleviate this problem, this paper efficiently and accurately detects obstacles regardless of lighting through DB-based feature matching. In addition, a criterion for classifying feature points is newly calculated by normalizing multiple planes to a single plane through RANSAC. As a result, the proposed method can efficiently detect obstacles regardless of lighting, natural light, and weather, and it is expected that it can be used to secure user safety because it can reliably detect surfaces in high and low or other terrains. In the proposed method, most of the experimental results on mobile devices reliably recognized indoor/outdoor obstacles.

Keywords

Mobile augmented reality; Obstacle detection; Feature matching; Multiplane; Human-computer interaction;

Citations & Related Records

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