For fast egomotion of a camera, computing feature correspondence and motion parameters by global search becomes highly timeconsuming. Therefore, the complexity of the estimation needs to be reduced for real-time applications. In this paper, we propose a compound omnidirectional vision sensor and an algorithm for estimating its fast egomotion. The proposed sensor has both multi-baselines and a l...

In a stereo image pair, the fundamental matrix encodes the rigidity constraint of the scene. It combines the internal parameters of both cameras (which can be the same) and their relative position and orientation. It associates to image points in one view the so-called epipolar line in the other view, which is the locus of projection of the same 3D point, whose particular position on the straig...

A novel face recognition scheme based on multi-stages classifier, which includes methods of support vector machine (SVM), Eigenface, and random sample consensus (RANSAC), is proposed in this paper. The whole decision process is conducted cascade coarse-to-fine stages. The first stage adopts one-against-one-SVM (OAO-SVM) method to choose two possible classes best similar to the testing image. In...

In typical sensor network applications, the sensors are left unattended for a long period of time. In addition, due to cost reasons, sensor nodes are usually not tamper resistant. Consequently, sensors can be easily captured and compromised by an adversary. Once compromised, a sensor can send authentique messages to other nodes and to the base station, but those messages may contain arbitrary d...

In several machine vision problems, a relevant issue is the estimation of homographies between two different perspectives that hold an extensive set of abnormal data. A method to find such estimation is the random sampling consensus (RANSAC); in this, the goal is to maximize the number of matching points given a permissible error (Pe), according to a candidate model. However, those objectives a...

Fault interpretation is an important part of seismic structural and reservoir characterization. In the conventional approach, faults are detected as reflection discontinuity or abruption manually tracked in post-stack data, which time-consuming. order to improve efficiency, a variety automatic fault detection methods have been proposed, among widespread attention has given deep learning-based m...

3D reconstruction applications can benefit greatly from knowledge about coplanar feature points. Extracting this knowledge from images alone is a difficult task, however. The typical approach to this problem is to search for homographies in a set of point correspondences using the RANSAC algorithm. In this work we focus on two open issues with a blind random search. First, we enforce the detect...

This work addresses the task of camera localization in a known 3D scene given a single input RGB image. State-of-the-art approaches accomplish this in two steps: firstly, regressing for every pixel in the image its 3D scene coordinate and subsequently, using these coordinates to estimate the final 6D camera pose via RANSAC. To solve the first step, Random Forests (RFs) are typically used. On th...

As-built building information modeling (BIM) model has gained more attention due to its increasing applications in construction, operation, and maintenance. Although methods for generating the as-built BIM from laser scanning data have been proposed, few studies were focused on full-scale structures. To address this issue, study proposes a semi-automated effective approach generate space frame ...

The increasing interest in digital twin technology, the digitalization of worn-out social overhead capital (SOC), and disaster management services has augmented usage 3D spatial models information to manage infrastructure. In this study, a subterranean utility tunnel was created, objects were identified using inbuilt image sensors. novelty lies development unique algorithm that breaks down stru...