基于图像与深度信息的室内视觉定位算法研究

哈尔滨工业大学工学硕士学位论文

Abstract

With the development of the city and the increasing use of smart phones, people's demand for indoor location is growing. GPS positioning method widely used in outdoor environments is difficult to apply in indoor environments due to the blockage and reflection. And the traditional indoor positioning methods such as WiFi and Bluetooth have high deployment cost. Therefore, taking into account the advantages of visual information and the user's convenience in acquiring scene visual information, positioning method based on vision receives extensive attention

This paper studies the research purpose and significance of indoor visual positioning. According to the relevant theoretical knowledge of camera modeling, feature descriptor extraction and pose solving algorithm in visual positioning system. The main research contents of this paper are as follow:

Firstly, aiming at the low positioning accuracy when traditional visual database building method only uses image information for positioning, this paper proposes a Visual-Depth Map database establishment method. This method introduces depth information into visual positioning database and reduces indoor positioning error.

Secondly, aiming at more redundant information when traditional database uses the point-by-point and video stream sampling, this paper proposes a database establishment method based on image keyframe algorithm. The original image sequence is selected to form a keyframe sequence based on image similarity. And the database is established by the keyframe sequences and depth information. Experimental results show that the database established by the image keyframe algorithm has a smaller database size under the same scene. As for positioning, this method reduces online positioning time while ensuring the positioning accuracy.

At last, aiming at feature point position error, the instability of iteration number, and the low accuracy when use the traditional algorithm based RANSAC to calculate the pose, this paper proposes a pose solving algorithm based on layered bundle adjustment. This algorithm processes the feature points by the layered manner to reduce the time complexity, and constructs the objective function by minimized reprojection error. The experimental results show that this algorithm has high accuracy in the calculation of pose, and reduces the positioning error.

Keywords: indoor positioning; visual positioning; database establishment; image keyframe; pose solving

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哈尔滨工业大学工学硕士学位论文

摘要 .......................................................................................................................... I Abstract ....................................................................................................................... II 第1章绪论 (1)

1.1课题研究的目的和意义 (1)

1.2国内外研究现状 (2)

1.2.1 室内定位技术研究现状 (2)

1.2.2 视觉定位技术研究现状 (4)

1.3本文的主要研究内容和结构安排 (7)

第2章视觉定位相关理论分析 (8)

2.1摄像机建模 (8)

2.1.1 视觉定位相关坐标系建立 (8)

2.1.2 位姿变换与相机外参 (9)

2.1.3 针孔成像模型与相机内参 (11)

2.1.4 Kinect相机配准 (13)

2.2视觉定位中图像特征描述子 (16)

2.2.1 全局特征描述子 (16)

2.2.2 局部特征描述子 (18)

2.3对极几何约束与EPnP算法 (20)

2.3.1 对极几何约束 (20)

2.3.2 EPnP算法 (22)

2.4本章小结 (24)

第3章基于图像关键帧的数据库建立方法 (25)

3.1基于图像关键帧的室内视觉定位系统 (25)

3.2图像关键帧选择算法 (26)

3.2.1 图像关键帧需求分析 (26)

3.2.2 图像关键帧选择算法 (28)

3.3性能分析 (31)

3.3.1图像关键帧算法性能分析 (31)

3.3.2基于图像关键帧的数据库建立方法性能分析 (36)

3.4本章小结 (39)

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哈尔滨工业大学工学硕士学位论文

4.1基于RANSAC的位姿求解算法 (40)

4.2基于RANSAC的位姿求解算法性能分析 (43)

4.3基于分层光束平差法的位姿求解算法 (46)

4.4性能分析 (54)

4.4.1基于分层光束平差法的位姿求解算法性能分析 (55)

4.4.2基于分层光束平差法的位姿求解算法在定位系统中的性能分析 (56)

4.5本章小结 (57)

结论 (59)

参考文献 (60)

攻读硕士学位期间发表的论文 (65)

哈尔滨工业大学学位论文原创性声明和使用权限 (66)

致谢 (67)

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