Landmark labeling of training images is essential for many learning tasks in computer vision, such as object detection, tracking, and alignment. Image labeling is typically conduc...
Yan Tong, Xiaoming Liu 0002, Frederick W. Wheeler,...
This contribution reports on ongoing collaborative research at the University of Stanford, Department of Psychology, and the University of Hamburg, Department for Informatics. Ext...
Fitting statistical 2D and 3D shape models to images is necessary for a variety of tasks, such as video editing and face recognition. Much progress has been made on local fitting...
In this paper, we examine the use of implicit shape representations for nonrigid registration of serial CT liver examinations. Using ground truth in the form of corresponding land...
Nathan D. Cahill, Grace Vesom, Lena Gorelick, Joan...
Abstract— This paper presents a new approach to the multirobot map-alignment problem that enables teams of robots to build joint maps without initial knowledge of their relative ...