A comparative study on pose estimation algorithms using visual data

Çetinkaya, Güven
Computation of the position and orientation of an object with respect to a camera from its images is called pose estimation problem. Pose estimation is one of the major problems in computer vision, robotics and photogrammetry. Object tracking, object recognition, self-localization of robots are typical examples for the use of pose estimation. Determining the pose of an object from its projections requires 3D model of an object in its own reference system, the camera parameters and 2D image of the object. Most of the pose estimation algorithms require the correspondences between the 3D model points of the object and 2D image points. In this study, four well-known pose estimation algorithms requiring the 2D-3D correspondences to be known a priori; namely, Orthogonal Iterations, POSIT, DLT and Efficient PnP are compared. Moreover, two other well-known algorithms that solve the correspondence and pose problems simultaneously; Soft POSIT and Blind- PnP are also compared in the scope of this thesis study. In the first step of the simulations, synthetic data is formed using a realistic motion scenario and the algorithms are compared using this data. In the next step, real images captured by a calibrated camera for an object with known 3D model are exploited. The simulation results indicate that POSIT algorithm performs the best among the algorithms requiring point correspondences. Another result obtained from the experiments is that Soft-POSIT algorithm can be considered to perform better than Blind-PnP algorithm.


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Perspective-n-Point (PnP) problem is the estimation of the pose (location and orientation) of a calibrated camera from 3D-2D point correspondences, that is, three-dimensional coordinates of objects in a world coordinate system and corresponding pixels in two-dimensional images. PnP algorithms are used in computer vision, augmented reality, robotics, photogrammetry etc. Distribution of the points in the image and the accuracy of the 3D information are important on the accuracy of the estimated pose of the ca...
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An active problem in digital geometry processing is shape interpolation which aims to generate a continuous sequence of in-betweens for a given source and target shape. Unlike traditional approaches that interpolate source and target shapes in isolation, recent data-driven approaches utilize multiple interpolations through intermediate database shapes, and consequently perform better at the expense of a database requirement. In contrast to the existing data-driven approaches that consider intermediate shape...
Citation Formats
G. Çetinkaya, “A comparative study on pose estimation algorithms using visual data,” M.S. - Master of Science, Middle East Technical University, 2012.