The most effective algorithms for model parameterisation in the presence of high noise, such as RANSAC, MINPRAN and Least Median Squares, use random sampling of data points to instantiate model hypotheses. However, their performance degrades in higher dimensionality due to the exponentially decreasing probability of sampling a set of inliers. It is suggested that biasing this random selection t...

Compared with traditional manned airborne photogrammetry, unmanned aerial vehicle remote sensing (UAVRS) has the advantages of lower cost and higher flexibility in data acquisition. It has, therefore, found various applications in fields such as three-dimensional (3D) mapping, emergency management, and so on. However, due to the instability of the UAVRS platforms and the low accuracy of the onb...

Capturing the dynamics of articulated models is becoming increasingly important. Dynamics, better than geometry, encode the functional information of articulated objects such as humans, robots and mechanics. Acquired dynamic data is noisy, sparse, and temporarily incoherent. The latter property is especially prominent for analysis of dynamics. Thus, processing scanned dynamic data is typically ...

Abstract. Feature Matching between images is an essential task for many computer vision and photogrammetry applications, such as Structure from Motion (SFM), Surface Extraction, Visual Simultaneous Localization Mapping (VSLAM), vision-based localization navigation. Among the matched point pairs, there are typically false positive matches. Therefore, outlier detection rejection important steps i...

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...

Airborne laser scanner technique is broadly the most appropriate way to acquire rapidly and with high density 3D data over a city. Once the 3D Lidar data are available, the next task is the automatic data processing, with major aim to construct 3D building models. Among the numerous automatic reconstruction methods, the techniques allowing the detection of 3D building roof planes are of crucial...

Robust fitting is a basic technique and has been widely applied in photogrammetry remote sensing, such as geometric correction. As known, typical robust estimators (include M-estimators, S-estimators, MM-estimators, etc.) often fail when outlier rate higher than 50%, even if the outliers are uniformly distributed. In this article, we propose simple yet effective estimators, called adaptive M-es...