This paper considers and solves the problem of estimating camera pose given a pair of point-tangent correspondences between the 3D scene and the projected image. The problem arises when considering curve geometry as the basis of forming correspondences, computation of structure and calibration, which in its simplest form is a point augmented with the curve tangent. We show that while the standa...

Pose estimation is an important operation for many robotic tasks such as camera calibration and landmark tracking. In this paper, we propose a new algorithm of pose estimation based on the volume measurement of tetrahedra composed of feature-point triplets extracted from an arba’trmy quadrangular target and the lenscenter of the vision system. This method has been tested using synthetic and rea...

Estimating the external calibration – the pose – of a camera with respect to its environment is a fundamental task in Computer Vision (CV). In this paper, we propose a novel method for estimating the unknown 6DOF pose of a camera with known intrinsic parameters from epipolar geometry only. For a set of geo-located reference images, we assume the camera position but not the orientation to be kno...

The goal of this paper is twofold: firstly, we propose a novel interpretation for collinearity in the process of camera pose estimation from given correspondences between a 3D model and its 2D projective image. In contrast with the existing interpretations for collinearity, the focus of expansion (FOE) theory is a special case of our novel interpretation for collinearity and besides the project...

We examine the potential use of gravity for camera calibration and pose estimation purposes. Concretely , objects being launched or dropped follow tra-jectories dictated by the law of gravity. We examine if video sequences of such trajectories give us exploitable constraints for estimating the imaging geometry. It is shown that it is possible to estimate the innnite homog-raphy and the epipolar...

In this paper, we propose a knowledge-guided pose grammar network to tackle the problem of 3D human pose estimation. Our model directly takes 2D poses as inputs and learns the generalized 2D-3D mapping function, which renders high applicability. The proposed network consists of a base network which efficiently captures pose-aligned features and a hierarchy of Bidirectional RNNs on top of it to ...

In this paper, we describe a method for estimating 3d pose of a human head from a 2d monocular web-cam image. We propose a novel system based on existing computer vision techniques for real-time head pose estimation, which can start and recover from failure automatically without any previous knowledge of the user’s appearance or location and keeping the user free of any devices or wires. The sy...

We present a new system for the automatic determination of the position , size and pose of the head of a human gure in a camera image. The system is an extension of the well{known face recognition system WFK] to pose estimation. The pose estimation system is characterized by a certain reliability and speed. We improve this performance and speed with the help of statistical estimation methods. I...

This paper presents the development of a lowcost sensor platform for use in ground-based visual pose estimation and scene mapping tasks. We seek to develop a technical solution using low-cost vision hardware that allows us to accurately estimate robot position for SLAM tasks. We present results from the application of a vision based pose estimation technique to simultaneously determine camera p...

A head pose estimation system is described, which uses low resolution video sequences to determine the orientation and position of a head with respect to a internally calibrated camera. The system employs a feature based approach to roughly estimate the head pose and an approach using a symmetry based illumination model to refine the head pose independent of the users albedo and illumination in...