A vision-based system for detecting and classifying moving obstacles in a cluttered environment using a single camera mounted on a small unmanned aerial vehicle is presented. Feature correspondences between successive image frames are found using the SIFT algorithm, and a model of the background motion is generated by Random Sample Consensus (RANSAC). The transformed frames are then differenced...

We have implemented a method that detects planar regions from 3D scan data using Random Sample Consensus (RANSAC) algorithm to address the issue of a tradeoff between the scanning speed and the point density of 3D scanning. However, the limitation of the implemented method has not been clear yet. In this paper, we conducted an additional experiment to evaluate the implemented method by changing...

This paper proposes an efficient pairwise surface matching approach for the automatic assembly of 3d fragments or industrial components. The method rapidly scans through the space of all possible solutions by a special kind of random sample consensus (RANSAC) scheme. By using surface normals and optionally simple features like surface curvatures, we can highly constrain the initial 6 degrees of...

In this paper, we present a novel image mosaicking method that is based on Speeded-Up Robust Features (SURF) of line segments, aiming to achieve robustness to incident scaling, rotation, change in illumination, and significant affine distortion between images in a panoramic series. Our method involves 1) using a SURF detection operator to locate feature points; 2) rough matching using SURF feat...

As Light Detection And Ranging (LiDAR) (point) data sets increase in resolution, earth scientists become more interested in detecting and delineating trees using LiDAR. The majority of conventional methods that detect and delineate trees convert point data into gridded surfaces. Unfortunately, this conversion process has the potential to introduce error. We improve a pointbased geometric model ...

Plane segmentation is a basic task in the automatic reconstruction of indoor and urban environments from unorganized point clouds acquired by laser scanners. As one of the most common plane-segmentation methods, standard Random Sample Consensus (RANSAC) is often used to continually detect planes one after another. However, it suffers from the spurious-plane problem when noise and outliers exist...

The intelligent use of green and renewable energies requires reliable preferably anticipated information regarding their availability the behavior meteorological variables in a scenario natural intermittency. Examples this are smart grids, which can incorporate, among others, charging system for electric vehicles modern predictive management techniques. However, some issues associated with such...

In this paper, we present a novel approach for stereo visual odometry with robust motion estimation that is faster and more accurate than standard RANSAC (Random Sample Consensus). Our method makes improvements in RANSAC in three aspects: first, the hypotheses are preferentially generated by sampling the input feature points on the order of ages and similarities of the features; second, the eva...

O registro de imagens é um problema comum na visão computacional com diversas aplicações que consiste em encontrar a correta transformação entre pares se sobrepõem. Neste trabalho objetiva-se apresentar modelo automático e preciso para utilizando o descritor SIFT método estimação RANSAC adaptado. ocorre através da estimativa homografia os imagens, utilizam as correspondências pontuais dadas pel...

The estimation of micro-Range (m-R) is important for micro-motion feature extraction and imaging, which provides significant supports the classification a precession cone-shaped target. Under low signal-to-noise ratio (SNR) circumstances, modified Kalman filter (MKF) will obtain broken segments rather than complete m-R tracks due to missing trajectories, performance MKF restricted by unknown no...