RANSAC (Random Sample Consensus) is a popular and effective technique for estimating model parameters in the presence of outliers. Efficient algorithms are necessary for both frame-rate vision tasks and offline tasks with difficult data. We present a deterministic scheme for selecting samples to generate hypotheses, applied to data from feature matching. This method combines matching scores, am...

We present a system that detects 3D mirror-symmetric objects in images and then reconstructs their visible symmetric parts. Our detection stage is based on matching mirror symmetric feature points and descriptors and then estimating the symmetry direction using RANSAC. We enhance this step by augmenting feature descriptors with their affinedeformed versions and matching these extended sets of d...

A model for tracking articulated objects is proposed using a novel 2D revolute-prismatic joint. An extension of the RANSAC and MLESAC algorithms incorporating feature weights is used to perform robust tracking. The models are suitable for tracking certain human body structures. Limbs are modelled as constrained planar patches. A patch can rotate about a joint point that is displaced relative to...

In this paper, a robust technique based on a genetic algorithm is proposed for estimating two-view epipolar-geometry of uncalibrated perspective stereo images from putative correspondences containing a high percentage of outliers. The advantages of this technique are three-fold: (i) replacing random search with evolutionary search applying new strategies of encoding and guided sampling; (ii) ro...

The moving least squares (MLS) and total (MTLS) are two of the most popular methods used for reconstructing measurement data, on account their good local approximation accuracy. However, reconstruction accuracy robustness will be greatly reduced when there outliers in data. This article proposes an improved MTLS method (IMTLS), which introduces random sample consensus (RANSAC) algorithm a corre...

This paper presents new techniques for simultaneous localization of multiple mobile robots using directional received signal strength (RSS). The RSS data is collected from the XBee wireless module with ZigBee technology. Directional RSS was achieved by a corner reflector antenna installed on the top of each mobile robot. The design parameters of the antenna were chosen by experiments and physic...

Given the influences of illumination, imaging angle, and geometric distortion, among others, false matching points still occur in all image registration algorithms. Therefore, false matching points detection is an important step in remote sensing image registration. Random Sample Consensus (RANSAC) is typically used to detect false matching points. However, RANSAC method cannot detect all false...

Point clouds registration is an important step for laser scanner data processing, and there have been numerous methods. However, the existing methods often suffer from low accuracy speed when registering large point clouds. To meet this challenge, improved iterative closest (ICP) algorithm combining random sample consensus (RANSAC) algorithm, intrinsic shape signatures (ISS), 3D context (3DSC) ...