Research On Methods For Dense Scene Reconstruction By Monocular Moving Camera

During the passed two decades, remarkable progress has been made in both numeric methods and hardware devices by related fields of computer graphic and image processing. By considering the scene reconstruction as the core mission, the interest of computer stereo vision community has been gradually shifted from sparse scene model to dense scene model. Currently, on the issue of implementing dense scene reconstruction by using monocular moving camera, systematic, efficient and adaptable method has yet been found, due the there dependency on initial conditions and complexity of the algorithm itself.Parts of the issue had been investigated, and three key-problems respectively from three main stages which could be divided from the solution has been solved.(1) A two-layer iterative estimation for fundamental matrix was proposed on initially observing stage which is in order to solve the key-problem of build correct geometric correspondence between two view. Wicked pose estimation and wrongly rectified images-pair can be triggered by incorrect geometric correspondence. By setting two-layer iterative model for passing the indirect parameters from external layer to inner layer, combined iterative linear estimation with seven points’ no-linear method, planar degeneration can be solved. The experiment shows that robust performance of the method can be demonstrated addition with some degree of adaptive parameter.(2) A multiple sequences’ solution for extending reconstruction was proposed on continuously observing stage which is in order to solve the problem of undermined system efficiency of observation and reconstruction by depth ambiguity. Depth ambiguity of short baseline system would be incrementing during the extending reconstruction by single sequence which can be considered as unavoidable. The efficiency of observation and reconstruction can be constantly lowing down until the system has to be terminated. By setting metric registration model combined with sequential extending reconstruction as subsystem, multi-way observation and unified reconstruction can be achieved. The experiment shows that the efficiency of sparse extending reconstruction can be improved.(3) A combined reconstruction with depth and motion was proposed on dense reconstruction stage which is in order to solve the problem of dependency on initial conditions in dense reconstruction. The method with high sensitivity on initial value can be hardly implemented under the monocular moving camera observation system which initial depth estimation could be inferior, addition with view changing and low frame-rate. By building an unified model for optimizing scene depth and spatial motion and implementing color-consistency error checking of texture synthesis, the dependency on initial value can be reduced. The experiment shows that the method can be used for implementing dense reconstruction under inferior initial conditions, meanwhile, the application range of motional field’s reconstruction has been expanded.