where Kθ is the matrix that warps latent image L to the transformed copy at a sampled pose θ and S denotes the set of sampled camera poses. While these algorithms show promising results, they entail high computational cost as the high-dimensional camera motion space and the latent image have to be computed during the iterative optimization procedures. In this paper, we propose a fast single-ima...

This paper addresses pose estimation problem for augmented reality applications in an urban environment. The pose is estimated based on the known wire-frame models of buildings and line segments detected on the images. One of key problems for model-based pose estimation is to establish the correspondence between the model and detected features. The main contribution of this paper is a robust ma...

Camera pose estimation is the problem of determining the position and orientation of an internally calibrated camera from known 3D reference points and their images. We introduce a new polynomial equation system for 4-point pose estimation and apply our symbolicnumeric method to solve it stably and efficiently. In particular, our algorithm can also recognize the points near critical configurati...

This papers presents a new system using circular markers to estimate the pose of a camera. Contrary to most markersbased systems using square markers, we advocate the use of circular markers, as we believe that they are easier to detect and provide a pose estimate that is more robust to noise. Unlike existing systems using circular markers, our method computes the exact pose from one single cir...

We present a method for estimating the distance between a camera and a human head in 2D images from a calibrated camera. Leading head pose estimation algorithms focus mainly on head orientation (yaw, pitch, and roll) and translations perpendicular to the camera principal axis. Our contribution is a system that can estimate head pose under large translations parallel to the camera’s principal ax...

Though a large body of computer vision research has investigated developing generic semantic representations, efforts towards developing a similar representation for 3D has been limited. In this paper, we learn a generic 3D representation through solving a set of foundational proxy 3D tasks: object-centric camera pose estimation and wide baseline feature matching. Our method is based upon the p...