Reconstructing a scene from many images has been an important problem in computer vision. Typically, 2D image feature points are detected, matched, and triangulated to …
Automatic recognition and segmentation of objects in images is a central open problem in computer vision. The failure of the segmentation-then-recognition paradigm to produce reliable …
Reconstructing 3D scenes from multiple views has made impressive strides in recent years, chiefly by correlating isolated feature points, intensity patterns, or curvilinear structures. In …
Many types of data observed in high dimensional spaces typically lie on or near low-dimensional manifolds and have much lower intrinsic dimension. Visual data captured …
Abstract of Multi-frame edge enrichment with SIFT flow, by Zijun Cui, Degree ScM., Brown University, May 2017. Edge information with high quality are desired by …
The image retrieval (IR) approach to image localization has distinct advantages to the 3D and the deep learning (DNN) approaches: it is seen-agnostic, simpler to …
This thesis develops new constraints for multiview 3D reconstruction, especially in relative pose estimation and dense reconstruction. Current multiview 3D reconstruction methods rely on two- …
Traditional visual odometry approaches often rely on estimating the world in the form a 3D cloud of points from keyframes, which are then projected onto …
Computer vision problems can be generally divided into three categories: recognition, reconstruction and reorganization. Specifically, reorganization problem is usually considered as a mid-stage process that …
Minimally Invasive Surgery (MIS) has been extensively employed in recent decades due to its capacity to minimize the trauma, decrease the recovery time, and enhance …
