Robust three-dimensional vehicle reconstruction using cross-ratio invariance PROJECT TITLE :Robust three-dimensional vehicle reconstruction using cross-ratio invarianceABSTRACT:A new method for structure-from-motion (SfM) is developed for moving vehicles on the street using a video camera Outdoor vehicle is one of the most difficult objects for tracking or three-dimensional (3D) reconstruction because most vehicle surfaces are specular and reflect background scenes. Therefore conventional point feature tracking method is not appropriate since spurious features are often tracked and the numbers of the correct features are too small. To overcome such difficulties, epipolar constraint, cross-ratio histogram and 3D curve reconstruction are employed in this method. The proposed method is also computationally efficient since it does not require expensive feature tracking process, which is used in most conventional SfM methods. Finally, to evaluate the error, experiments over 200 vehicles are performed under various viewing conditions and they show significant correlation among the number of frames, distance from the camera and accuracy of reconstruction. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Partial differential equation-based dense 3D structure and motion estimation from monocular image sequences Recognising human actions by analysing negative spaces
