To solve the problem of relative camera pose estimation, a method using optimization with respect to the manifold is proposed. Firstly from maximum-a-posteriori (MAP) model to nonlinear least squares (NLS) model, the general state estimation model using optimization is derived. Then the camera pose estimation model is applied to the general state estimation model, while the parameterization of ...

A method is introduced to track the object’s motion and estimate its pose from multiple cameras. Firstly pose estimation from one camera is explained. We show that pose estimation from the corresponding feature points can be formed as a solution to Sylvester’s equation. Furthermore, we develop a distributed solution, which indicates that pose estimation from multiple cameras can be obtained fro...

In this document, we present methods to camera pose estimation from one single images in a known environment. The framework of such methods comprises two stages, a learning step and an inference stage where given a new image we recover the exact camera position. This research work focus on achieving such a task with the help of lines and the Radon/Hough transform. The question to be answered in...

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 briefly survey several existing methods for pose estimation, then introduce our new improved linear algorithm. The advantage of the algorithm is that it is easy to implement and stable. We give the experimental results.

This paper presents a novel approach for the extrinsic parameter estimation of omnidirectional cameras with respect to a 3D Lidar coordinate frame. The method works without specific setup and calibration targets, using only a pair of 2D-3D data. Pose estimation is formulated as a 2D-3D nonlinear shape registration task which is solved without point correspondences or complex similarity metrics....

In this paper, we address the problem of 3D human body pose estimation from depth images acquired by a stereo camera. Compared to the Kinect sensor, stereo cameras work outdoors having a much higher operational range, but produce noisier data. In order to deal with such data, we propose a framework for 3D human pose estimation that relies on random forests. The first contribution is a novel gri...

In this work we present a unified method of relative camera pose estimation from points and lines correspondences. Given a set of 2D points and lines correspondences in three views, of which two are known, a method has been developed for estimating the camera pose of the third view. Novelty of this algorithm is to combine both points and lines correspondences in the camera pose estimation which...