The Research and Application of Improved ORB Feature Matching Algorithm

Liu, Chang; Shu-wen, Dang

doi:10.1007/978-981-19-6613-2_413

Cited by 2 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Currently, methods based on visual SLAM (Simultaneous Localization and Mapping) have been widely applied to the 3D reconstruction of indoor and outdoor environments [5] . The ORB-SLAM feature-based visual SLAM algorithm has good robustness, real-time performance, and locality [6] .…”

Section: Introductionmentioning

confidence: 99%

Cultural relic reconstruction device based on ORB-SLAM

Yang,

Sun

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

ORB-SLAM, an advanced visual SLAM technology, has excellent positioning and mapping capabilities [1]. In the reconstruction of cultural relics, ORB-SLAM technology can achieve autonomous perception and modeling of the surrounding environment of cultural relics by fusing and analyzing the images of monocular depth cameras, thereby reconstructing the 3D model of cultural relics, providing new possibilities for the protection and inheritance of cultural relics. Point cloud images are a digital technology used for 3D modeling, which can save point data on object surfaces and their relationships as 3D point clouds [2]. In terms of cultural relic reconstruction, point cloud images can restore and reconstruct the shape, size, texture, and other features of cultural relics by processing the collected point data on the surface of cultural relics into a 3D model. The purpose of this device is to reconstruct cultural relics by generating point cloud images based on ORB-SLAM technology. Combined with the designed handheld pan tilt device, it can achieve multi-angle point cloud mapping of cultural relics scenes in complex terrain. This paper will introduce the handheld gimbal design of the device, the realization of point cloud mapping based on the ORB-SLAM3 algorithm [3], and the application of point cloud scenes. Through the research in this article, it is expected to provide a new and efficient method for cultural relic reconstruction in the field of cultural relic protection and make contributions to the protection and inheritance of cultural heritage.

show abstract

Section: Introductionmentioning

confidence: 99%

Cultural relic reconstruction device based on ORB-SLAM

Yang,

Sun

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…When the feature points are too dense, redundant, and have poor uniformity, it will result in low SLAM positioning accuracy and computational efficiency. When feature points are too sparse, difficulties will be encountered in matching feature points [2].…”

Section: Introductionmentioning

confidence: 99%

Analysis of feature point matching technology in SLAM based on binocular vision

Yu¹

2023

HSET

View full text Add to dashboard Cite

With rapidly developing computing technology, intelligent robots have been used extensively in many areas of life, improving work efficiency and lowering labor costs. At the same time, with the increasing number of robot application scenarios, the demand for robot intelligence has also increased. Computer vision-based simultaneous localization and mapping (SLAM) technology is a key technology that helps robots achieve real-time positioning and navigation in order to improve their intelligence. Feature point matching is an important component of this technology. This paper mainly analyzes the current development status of feature point matching technology in visual SLAM. Firstly, a brief introduction was given to the three widely used SLAMs, and the advantages and disadvantages of different SLAM technologies were analyzed. Second, a brief presentation and explanation of the working principle of binocular SLAM technology were provided. Then, the basic principles and key points of feature point recognition and matching techniques in several different algorithms for visual SLAM were summarized. Analyzed the advantages and disadvantages of various algorithms, as well as improvements based on this algorithm. Finally, summarize and provide suggestions for the future development of visual SLAM technology.

show abstract

The Research and Application of Improved ORB Feature Matching Algorithm

Cited by 2 publications

References 7 publications

Cultural relic reconstruction device based on ORB-SLAM

Cultural relic reconstruction device based on ORB-SLAM

Analysis of feature point matching technology in SLAM based on binocular vision

Contact Info

Product

Resources

About