SIA OpenIR  > 机器人学研究室
Alternative TitleMoving Object Tracking Based on Multi-sensor Fusion
Thesis Advisor田建东
Keyword联合标定 图像配准 多传感器融合 目标检测与跟踪
Call NumberTP391.41/H78/2018
Degree Discipline模式识别与智能系统
Degree Name硕士
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Other AbstractWith the development of machine vision, moving objects tracking has become a hot spot and a key in the field of this research. It is widely used in human-computer interaction, virtual reality, video surveillance, robot navigation, intelligent vehicles and so on, but under the complex and changeable light and weather conditions, the application of the visual sensor has some limitations, and the multi-sensor fusion can realize the information complementation. It has good fault tolerance, real-time and robustness compared to the single sensor. The main research contents are as follows. First of all, the development of multi-sensor registration and fusion algorithm is briefly introduced. The basic theory of image registration algorithm and the type of registration are introduced in detail. The basic theory of multi-sensor registration and fusion algorithm is elaborated. Secondly, the principle of millimeter-wave radar detection, data receiving and analysis methods are introduced, and a method for filtering out false objects by millimeter-wave radar is proposed. A joint calibration method for visual sensor and millimeter-wave radar system is introduced. The transformation relationships among world coordinate system, vision sensor coordinate system, image physical coordinate system and pixel coordinate system are constructed, spatial registration transformation relationship between millimeter-wave radar and visual sensor is obtained. On the basis of this, the space-time registration is completed with time registration method. Then, object registration in infrared images and visible images is studied. In heterogeneous image fusion, due to different shooting conditions, shooting time and imaging principle, registration method is difficult. The two images are pre-processed respectively by using the hybrid Gauss model to obtain shape contour of objects. Bipartite graph matching is established for the contour points of the two preprocessed images. In order to extend match to the whole shape, a TPS transformation model is established. A regularization method is used to relax the interpolation requirements, and the estimation error is reduced by iteratively reorganizing corresponding relationship and estimating the transformation. RANSAC algorithm is used to filter out wrong matching points, and make the tracking result more reliable. Finally, object detection is carried out by using the adaptive background subtraction method, fusion system is used to simulate moving object tracking in actual environment, and the practical application effect of the sensing system based on millimeter-wave radar and vision sensor, infrared thermal imager and camera is verified. The feasibility and effectiveness of the proposed moving object tracking method based on multi-sensor fusion are analyzed, which provide experimental basis for the subsequent system improvement.
Contribution Rank1
Document Type学位论文
Recommended Citation
GB/T 7714
黄微. 基于多传感器融合的运动目标跟踪[D]. 沈阳. 中国科学院沈阳自动化研究所,2018.
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基于多传感器融合的运动目标跟踪.pdf(3084KB)学位论文 开放获取CC BY-NC-SAApplication Full Text
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