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스마트폰을 이용한 위치정보기반 AR 시스템에서의 부정합 현상 최소화를 위한 기법

Error Correction Scheme in Location-based AR System Using Smartphone

  • 투고 : 2014.09.16
  • 심사 : 2015.04.10
  • 발행 : 2015.04.30

초록

스마트폰의 보급 확산으로 다양한 콘텐츠가 등장하고 있다. 이러한 콘텐츠 중에서 위치 기반 서비스를 이용한 증강현실 응용프로그램의 필요성이 널리 대두되고 있다. 본 논문에서는 안드로이드 스마트폰을 이용한 위치정보기반 AR 시스템에서 발생하는 정합 오차를 컴퓨터 비전 기술을 이용하여 효과적으로 줄이는 방법을 제안한다. 위치정보 오차 누적 때문에 객체가 정확하게 정합되지 않는 부정합 현상 최소화를 위해 연산 속도는 유지하면서 연산량을 줄여 성능을 향상한 방법인 SURF(Speeded Up Robust Features)를 사용해 초기 특징점을 검출하고 검출된 특징점을 추적하여 모바일 환경에 적용한다. 위치정보 검색을 위해 GPS 정보를 사용하고 자세추정 및 방향 정보를 위해 자이로 센서, G-센서 등을 이용한다. 하지만 위치정보의 누적된 오차는 객체가 고정되지 않는 부정합 현상을 유발한다. 또한, 증강현실 기술은 구현하면서 많은 연산량이 필요하므로 모바일 환경에서 구현하는데 어려움이 발생한다. 제안된 방법은 모바일 환경에서 성능 저하를 최소화하고 비교적 간단하게 구현할 수 있어 기존 시스템 및 다양한 모바일 환경에서 유용하게 이용될 수 있다.

Spread of smartphone creates various contents. Among many contents, AR application using Location Based Service(LBS) is needed widely. In this paper, we propose error correction algorithm for location-based Augmented Reality(AR) system using computer vision technology in android environment. This method that detects the early features with SURF(Speeded Up Robust Features) algorithm to minimize the mismatch and to reduce the operations, and tracks the detected, and applies it in mobile environment. We use the GPS data to retrieve the location information, and use the gyro sensor and G-sensor to get the pose estimation and direction information. However, the cumulative errors of location information cause the mismatch that and an object is not fixed, and we can not accept it the complete AR technology. Because AR needs many operations, implementation in mobile environment has many difficulties. The proposed approach minimizes the performance degradation in mobile environments, and are relatively simple to implement, and a variety of existing systems can be useful in a mobile environment.

키워드

참고문헌

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피인용 문헌

  1. 다중 시구간 신경회로망을 이용한 인간 행동 인식 vol.18, pp.3, 2015, https://doi.org/10.9728/dcs.2017.18.3.559
  2. A Study on Tracking and Augmentation in Mobile AR for e-Leisure vol.2018, pp.None, 2018, https://doi.org/10.1155/2018/4265352