This paper investigates passivity-based visual feedback pose regulation whose goal is to control a vision camera pose so that it reaches a desirable configuration relative to a moving target object. For this purpose, we present a novel visual feedback estimation/control structure including a vision-based observer called visual motion observer under the assumption that a pattern of the target mo...

Estimation of a camera pose (position and orientation) from an image, given a 3d model of the world, is a topic of great interest in many current fields of research. When aiming for a model based pose estimation approach, several questions arise: What is the model? How do we acquire a model? How is the image linked to the model? How is a pose computed and verified using the latter information? ...

In this paper, a new method is proposed to estimate the pose of a moving vehicle in a typical traffic scene. Pose determination is crucial in the process of fitting or matching an existing 3D model in the database with the captured moving object. In this work, pose estimation is determined by estimating the 3D position of the moving vehicle in world space and then computing the motion vector of...

This paper addresses the problem of estimating the 3-D trajectory and associated uncertainty of an underwater autonomous vehicle from a set of images of the seabed taken by an onboard camera. The presented algorithms resort to the use of video mosaics and build upon previous work on image registration and visual pose estimation. The pose estimation is accomplished in two steps. Firstly a video ...

Robotic navigation requires that the robotic platform have an idea of its location and orientation within the environment. This localization is known as pose estimation, and has been a much researched topic. There are currently two main categories of pose estimation techniques: pose from hardware, and pose from video (PfV). Hardware pose estimation utilizes specialized hardware such as Global P...

We present PPnP, an algorithm capable of estimating a robust camera pose in real-time, even if being provided with large sets of correspondences containing high ratios of outliers. For these situations, standard pose estimation algorithms using RANSAC are often unable to provide a solution or at least not in the required time frame. PPnP is provided with a probability distribution function whic...

An Augmented Reality (AR) system on mobile phones has recently attracted attention because smartphones have increasingly been popular. For an AR system, we have to know a camera pose of a smartphone. A sensor-based method is one of the most popular ways to estimate the camera pose, but it cannot estimate an accurate pose. A vision-based method is another way to estimate the camera pose, but it ...

We describe a new pose estimation approach for a 3D object capture system. This 3D pose estimation approach offers several advantages: increased visibility, robustness to lighting conditions, and improved reliability with evenly distributed errors. The calibration pattern is built using 3D conic features. We use simplex search to find the camera position and orientations that minimizes the erro...

Recently, Tuceryan and Navab introduced a method for calibrating an optical see-through system based on the alignment of a set of 2D markers on the display with a single point in the scene while not restricting the user’s head movements (the single point active alignment method or SPAAM in short) [33]. This method is applicable with any tracking system, provided that it gives the pose of the se...