Robust three-dimensional vehicle reconstruction using cross-ratio invariance


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

PROJECT TITLE : Accurate and Robust Video Saliency Detection via Self-Paced Diffusion ABSTRACT: In order to estimate video saliency in the short term, traditional video saliency detection algorithms usually follow the common
PROJECT TITLE : Robust Lane Detection from Continuous Driving ScenesUsing Deep Neural Networks ABSTRACT: For autonomous vehicles and sophisticated driver assistance systems, lane recognition in driving scenes is a critical element.
PROJECT TITLE : Robust Unsupervised Multi-view Feature Learning with Dynamic Graph ABSTRACT: By modeling the affinity associations with a graph to lower the dimension, graph-based multi-view feature learning algorithms learn a
PROJECT TITLE : A Spatially Constrained Probabilistic Model for Robust Image Segmentation ABSTRACT: In probabilistic model based segmentation, the hidden Markov random field (HMRF) is used to describe the class label distribution
PROJECT TITLE : An Adaptive and Robust Edge Detection Method Based on Edge Proportion Statistics ABSTRACT: One of the most important preprocessing steps for high-level tasks in the field of image analysis and computer vision is

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry