http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Xiangsai Feng (검색결과 1 건)
- 무료
- 기관 내 무료
- 유료
-
Loop Closure Detection Based on Image Covariance Matrix Matching for Visual SLAM
Tao Ying,Huaicheng Yan,Zhichen Li,Kaibo Shi,Xiangsai Feng 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.11
Loop closure detection is an indispensable part of visual simultaneous location and mapping (SLAM). Correct detection of loop closure can help mobile robot to reduce the problem of cumulative pose drift. At present, the main method for detecting visual SLAM loop closure is the bag of words (BoW) model, but it lacks the spatial distribution information of local features of the image, and the scale will become larger and larger with the increase of data, resulting in the slow operation speed. In order to solve these problems, the image histogram and the key region covariance matrix matching method are used to visually detect the loop closure combined with the global and local image features. In this paper, three different place recognition techniques are studied: histogram only, image covariance matrix matching (ICMM) and cluster loop. Experiments on real datasets show that the proposed method of detecting the loop closure is better than the traditional methods in detecting accuracy and recalling rate, which also improves the operation effect of the SLAM algorithm.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
