The Research Of Image Sequences Based Position And Orientation Determination

Self-position and orientation of moving platform play a vital role in deep space exploration, indoor robot control and other application. Image-based self-position and orientation technology for moving platform is an arisen technology. It is a widely used for3D position and orientation estimation, and it provides the relative space benchmark for registration and fusion of other sensor data. Adopting such technology, the thesis reports the study in detail as follows:1) The relative positioning and orientation methods based on two or three-views have been studied thoroughly. This two or three-view geometry is the foundation of self-position and orientation from monocular image sequence. Besides, for stereo images,3D point clouds and relative position and orientation change estimation method based on these points are also discussed.2) The relative positioning and orientation for monocular image sequences and stereo image sequences have been detailed studied. For relative positioning and orientation, there are four methods as follows.a) The method based on two-view geometry with consecutive two images. In this situation, relative orientation change can be obtained with real angle relative to the last image. But the relative position change can be obtained without global consistent scale.b) The method based on two-view geometry with every other two images. In this situation, two-view geometry is calculated in every other two images. The image between the two images can be used to transfer the scale to the next triple images. So camera moving trajectory with a global consistent scale can be obtained.c) The method based on two-view geometry with consecutive three images. In this situation, two-view geometry is calculated one another in this triple images. The three displacement vectors can form a close vector triangle. With this constrain, moving trajectory with a global consistent scale can be recovered.d) The method based on trifocal tensor with consecutive three images. When the trifocal tensor has been calculated, camera projection matrixes of the three images are also obtained. With these matrixes, camera’s relative position and orientation are recovered consecutively.3) The relative positioning and orientation method based on monocular and stereo image sequences. On the one hand, using stereo image sequence, the real displacement in monocular image sequence can be obtained, and the accumulation error can be reduced. On the other hand, using monocular image sequence, the temporal sampling rate of stereo image sequence can be increased.4) The methods of corresponding point detection in image sequence have been introduced. For single camera video stream, feature point tracking method has been applied, and key frame selection step has been used for increase the stability and reliability of two-view geometry calculation. For both single camera image sequence and stereo camera image sequence, feature point detection and matching method have been applied. Besides, the corresponding point between two point clouds has been found through feature point matching between two stereo image pairs.5) Computer simulation image sequences and real image sequences have been applied to test the proposed relative positioning and orientation methods. Simulation test can provide the ground truth for comparison with the recovered moving trajectory, and real image sequences test can evaluate the method’s feasibility, efficiency and stability when it has been applied in mobile mapping system.The innovation of this search is as follows.1) Only image based relative positioning and orientation method has been proposed. Compared to those existing methods with image, this search has two characteristics:①It’s fully image-based method and independent on other range finding sensor, or positioning and orientation sensor;②the relative positioning and orientation is in3D space, not localization and heading only in plane.2) Four relative positioning and orientation methods based on monocular image sequence have been proposed and the comparison with one another has been made. Besides, their demands on corresponding points and movement have been studied. The stereo image has been used to calculate the relative position and orientation, not only reconstruct the3D scene structure. The corresponding point between two point clouds has been found through feature point matching between two stereo image pairs.3) The method which combines monocular image sequence based method with stereo image sequence based method has been proposed. This hybrid method can take the advantages of both high temporal sampling rates from single video camera and real displacement from stereo camera. It can produce high precision, high stability and high reliability results of relative position and orientation.