Particle filtering is a very popular technique for sequential state estimation. However, in high-dimensional cases where the state dynamics are complex or poorly modeled, thousands of particles are usually required for real applications. This paper presents a hybrid sampling solution that combines RANSAC and particle filtering. In this approach, RANSAC provides proposal particles that, with hig...

We present a system for automatically detecting obstacles from a moving vehicle using a monocular wide angle camera. Our system was developed in the context of finding obstacles and particularly children when backing up. Camera viewpoint is transformed to a virtual bird-eye view. We developed a novel image registration algorithm to obtain ego-motion that in combination with variational dense op...

This chapter describes a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three main stages. Initially, feature points are extracted and ...

Many existing approaches used iterative-reenement techniques for 3D registration of partially-overlapping range images. The major drawback of these approaches is that they require a good initial estimate to guarantee that the correct solution can always be found. In this paper, we propose a new method, the RANSAC-based DARCES (data-aligned rigidity-constrained exhaustive search) method, which c...

Random Sample Consensus (RANSAC) [3] has been popular in regression problem with samples contaminated with outliers. M-estimator, Hough transform, and others had been utilized before RANSAC. However, RANSAC does not use complex optimization as like M-estimator. It does not need huge amounts of memory as like Hough transform to keep parameter space. RANSAC is simple iteration of two steps: hypot...

A new algorithm is proposed to accelerate the RANSAC model quality calculations. The method based on partitioning joint correspondence space, e.g., 2D-2D point correspondences, into a pair of regular grids. grid cells are mapped by minimal sample models, estimated within RANSAC, reject correspondences that inconsistent with parameters early. technique general. It works arbitrary transformations...

The estimation of the transformation parameters between different point clouds is still a crucial task as it is usually followed by scene reconstruction, object detection or object recognition. Therefore, the estimates should be as accurate as possible. Recent developments show that it is feasible to utilize both the measured range information and the reflectance information sampled as image, a...

With the development of Building Information Modelling (BIM) and Terrestrial Laser Scanning (TLS) in the Architecture, Engineering, Construction & Facility Management (AEC/FM) industry, the registration of site laser scans and project 3D (BIM) models in a common coordinate system is becoming critical to effective project control. The co-registration of 3D datasets is normally performed in two s...

As an all-weather and all-day remote sensing image data source, SAR (Synthetic Aperture Radar) images have been widely applied, their registration accuracy has a direct impact on the downstream task effectiveness. The existing algorithms mainly focus small sub-images, there is lack of available accurate matching methods for large-size images. This paper proposes high-precision, rapid, dense-mat...

Image registration is a fundamental image processing task to match and align physically two images which could have been imaged by different sensors, view angles or and at different times. It is necessary to have robust single frame image registration software especially an automated one. Automatic image registration framework overlays two images for geometric conformity aligning common feature...