Dual Quaternion Particle Filtering for Pose Estimation

Pose and Motion Estimation Using Dual quaternion-based Extended Kalman Filtering

Fast Feature-Less Quaternion-based Particle Swarm Optimization for Object Pose Estimation From RGB-D Images

We present a novel quaternion-based formulation of Particle Swarm Optimization for pose estimation which, differently from other approaches, does not rely on image features or machine learning. The quaternion formulation avoids the gimbal lock problem, and the objective function is based on raw 2D depth information only, under the assumption that the object region is segmented from the backgrou...

Dual Generative Models for Human Pose Estimation

Given a image photographed somebody in action, we describe a dual-generative-model approach for estimating human body pose from silhouette. In contrast to existing techniques, which mostly learn regression model whereby make inference of body pose for unknown input [1, 2, 6, 7], we transform the problem into searching of the best pair of upper pose and lower pose. This searching strategy can re...

Quaternion Based Camera Pose Estimation From Matched Feature Points

We present a novel solution to the camera pose estimation problem, where rotation and translation of a camera between two views are estimated from matched feature points in the images. The camera pose estimation problem is traditionally solved via algorithms that are based on the essential matrix or the Euclidean homography. With six or more feature points in general positions in the space, ess...

Particle Filtering Range Data for Pose Estimation under Torque-free Motion

Autonomous rendezvous and capture is a current research interest with varied mission applications ranging from servicing to sample return. Especially interesting is the problem of rendezvous with an uncooperative tumbling target in orbit. One key to this process is the ability to estimate the relative pose and motion of the target object. This paper presents a particle filter method which utili...