Reconstruction of 3D scenes using stereoimages without rectification

The problem of reconstructing 3D scenes using stereopairs of images is considered. In contrast to traditional technologies whereby the rectification and disparity map construction are implemented, the corresponding points are determined directly on the epipolar lines that belong to the given epipolar plane. A complete three-dimensional model of an object is constructed by scanning a 3D scene using pencils of planes. The elimination of fragment-matching errors occurs by using the decimation filtering of the found points. The results of experiments that show the efficiency of the proposed technology are provided.     

Visual SLAM Based on Rigid-Body 3D Landmarks

In current visual SLAM methods, point-like landmarks (As in Filliat and Meyer (Cogn Syst Res 4(4):243–282, 2003), we use this expression to denote a landmark generated by a point or an object considered as punctual.) are used for representation on maps. As the observation of each point-like landmark gives only angular information about a bearing camera, a covariance matrix between point-like landmarks must be estimated in order to converge with a global scale estimation. However, as the computational complexity of covariance matrices scales in a quadratic way with the number of landmarks, the maximum number of landmarks that is possible to use is normally limited to a few hundred. In this paper, a visual SLAM system based on the use of what are called rigid-body 3D landmarks is proposed. A rigid-body 3D landmark represents the 6D pose of a rigid body in space (position and orientation), and its observation gives full-pose information about a bearing camera. Each rigid-body 3D landmark is created from a set of N point-like landmarks by collapsing 3N state components into seven state components plus a set of parameters that describe the shape of the landmark. Rigid-body 3D landmarks are represented and estimated using so-called point-quaternions, which are introduced here. By using rigid-body 3D landmarks, the computational time of an EKF-SLAM system can be reduced up to 5.5%, as the number of landmarks increases. The proposed visual SLAM system is validated in simulated and real video sequences (outdoor). The proposed methodology can be extended to any SLAM system based on the use of point-like landmarks, including those generated by laser measurement.     

Visual 3-D SLAM from UAVs

The aim of the paper is to present, test and discuss the implementation of Visual SLAM techniques to images taken from Unmanned Aerial Vehicles (UAVs) outdoors, in partially structured environments. Every issue of the whole process is discussed in order to obtain more accurate localization and mapping from UAVs flights. Firstly, the issues related to the visual features of objects in the scene, their distance to the UAV, and the related image acquisition system and their calibration are evaluated for improving the whole process. Other important, considered issues are related to the image processing techniques, such as interest point detection, the matching procedure and the scaling factor. The whole system has been tested using the COLIBRI mini UAV in partially structured environments. The results that have been obtained for localization, tested against the GPS information of the flights, show that Visual SLAM delivers reliable localization and mapping that makes it suitable for some outdoors applications when flying UAVs.     

A practical 2D/3D SLAM using directional patterns of an indoor structure

This paper presents a practical two-dimensional (2D)/three-dimensional (3D) simultaneous localization and mapping (SLAM) algorithm using directional features for ordinary indoor environments; this algorithm is adaptable to various conditions, computationally inexpensive, and accurate enough to use for practical applications. The proposed algorithm uses odometry acquired from other sensors or other algorithms as the initial estimate and the directional features of indoor structures as landmarks. The directional features can only correct the rotation error of the odometry. However, we show that the greater part of the translation error of the odometry can also be corrected when the directional features are detected at almost positions accurately. In that case, there is no need to use other kinds of features to correct translation error. The directions of indoor structures have two advantages as landmarks. First, the extraction of them is not affected by obstacles. Second, the number of them is small regardless of the size of the building. Because of these advantages, the proposed SLAM algorithm shows robustness for parameters and lightweight properties. From extensive experiments with 2D/3D datasets taken from different buildings, we show the practicality of the proposed algorithm. We also demonstrate that the 2D algorithm runs in real time on a low-end smartphone.     

基于2D激光雷达的SLAM算法研究综述

移动机器人导航功能的实现需要同时定位与建图(simultaneous localization and mapping,SLAM)和路径规划这两方面的技术,其中由SLAM技术生成的栅格地图是移动机器人运用路径规划算法的前提。2D激光SLAM由于其建图精度较高、性能稳定且价格便宜,在室内移动机器人中应用十分广泛。2D激光SLAM是指移动机器人在自身所处环境及位置先验信息未知的情况下,以2D激光雷达为主要传感器,感知周围环境信息,从而实现自身位姿的估计和地图的构建。将2D激光SLAM分为两部分,第一部分从激光测距原理入手,对三角法和飞行时间法进行了详细介绍和优缺点比较。第二部分从前端扫描匹配、后端优化、回环检测和地图构建这四个方面分别详细阐述了2D激光SLAM系统框架。同时对主流2D激光SLAM算法进行了深入分析和优缺点比较,并对激光SLAM未来的发展进行了展望。     

Information-Efficient 3-D Visual SLAM for Unstructured Domains

This paper presents a novel vision-based sensory package and an information-efficient simultaneous localization and mapping (SLAM) algorithm. Together, we offer a solution for building 3-D dense map in an unknown and unstructured environment with minimal computational costs. The sensory package we adopt consists of a conventional camera and a range imager, which provide range and bearing and elevation inputs as commonly used by 3-D feature-based SLAM. In addition, we propose an algorithm to give the robots the `intelligence” to select, out of the steadily collected data, the maximally informative observations to be used in the estimation process. We show that, although the actual evaluation of information gain for each frame introduces an additional computational cost, the overall efficiency is significantly increased by keeping the matrix compact. The noticeable advantage of this strategy is that the continuously gathered data are not heuristically segmented prior to being input to the filter. Quite the opposite, the scheme lends itself to be statistically optimal and is capable of handling large datasets collected at realistic sampling rates.      

低成本移动机器人2D SLAM算法地图评估研究

随着传感器技术的发展,移动机器人得到了广泛的应用.用于绘制环境地图的2D SLAM技术是移动机器人领域重要的技术之一,选出适合低成本机器人的算法对机器人的发展和普及至关重要.提出在仿真环境和实际场景下运行广泛使用的四种开源算法:Gmapping、Hector SLAM、Karto SLAM和Google Cartogr...     

二维概念格图形的三维重构研究

介绍了二维概念格图形向三维空间转化和延伸的必要性和现状。通过对传统概念格图形分层定位布局方法的研究与分析,提出并实现了一种新的以具有大量的平行四边形和有向线段为基本特征的概念格在三维空间的自动布局算法,描述了一种基于该算法的二维概念格图形的三维重构机制,有效地解决了节点横向过度扩张的问题并减少了线段交叉,较好地实现了复杂概念格图形的三维可视化,为知识发现和知识处理提供了良好的基础。     

二维概念格图形的三维重构研究

介绍了二维概念格图形向三维空问转化和延伸的必要性和现状.通过对传统概念格图形分层定位布局方法的研究与分析,提出并实现了一种新的以具有大量的平行四边形和有向线段为基本特征的概念格在三维空间的自动布局算法,描述了一种基于该算法的二维概念格图形的三维重构机制,有效地解决了节点横向过度扩张的问题并减少了线段交叉,较好地实现了复杂概念格图形的三维可视化,为知识发现和知识处理提供了良好的基础.     

采用SLAM方法的电脑鼠

与绝大部分采用红外对管进行简单测距的电脑鼠不同,在电脑鼠上使用线型激光器和摄像头搭建了一个小型激光测距系统并进行SLAM。摄像头以240 f/s的帧率输出分辨率为188×120的图像,使用Zynq-7010作为主控制器,在其可编程逻辑部分搭建了图像采集系统,在其双核处理器Cortex-A9部分搭建了用于运行图像处理、传感器数据融合和解迷宫算法的实时Linux操作系统。制作了一只重量为100.06 g、车体大小为7.45 cm(宽)×6.6 cm(长)的电脑鼠,能高速稳定地在迷宫中运动。     

Transformations between Pictures from 2D to 3D

This paper describes programs for 3-dimensional engraving. The programs use raster or vector images to create a 3D model and, subsequently, convert this model into a sequence of control commands for 3D engraving machines. Three programs have been developed. A program for engraving general 3D surfaces from grey-scale images, a program for preparing these grey-scale images from patterns and vector images, and a program for fast 2D engraving. A simple and fast preparation of the 3D model, a user-friendly environment, and small hardware requirements were the principal goals.     

3D foot shape generation from 2D information

Two methods to generate an individual 3D foot shape from 2D information are proposed. A standard foot shape was first generated and then scaled based on known 2D information. In the first method, the foot outline and the foot height were used, and in the second, the foot outline and the foot profile were used. The models were developed using 40 participants and then validated using a different set of 40 participants. Results show that each individual foot shape can be predicted within a mean absolute error of 1.36 mm for the left foot and 1.37 mm for the right foot using the first method, and within a mean absolute error of 1.02 mm for the left foot and 1.02 mm for the right foot using the second method. The second method shows somewhat improved accuracy even though it requires two images. Both the methods are relatively cheaper than using a scanner to determine the 3D foot shape for custom footwear design.     

Extending distortion viewing from 2D to 3D

Addresses the visual exploration of 3D information layouts. Several visual exploration techniques have been proposed for 2D information layouts. Many of these try to take advantage of humans' natural visual pattern-recognition abilities to understand global relationships while simultaneously integrating this knowledge with local details. This desire for detail-in-context views (also called fisheye, multiscale and distortion views) has fueled considerable research in the development of distortion viewing tools. Generally, these tools provide space for magnification of local detail by compressing the rest of the image. In considering a possible detail-in-context view for 3D layouts, we first examine 2D distortion techniques, bearing in mind the particular 3D problem of occlusion. Comparing 2D and 3D information layout adjustment tools leads directly to a 3D visual access tool that clears a line of sight to any region of interest. While our technique can extend to any type of 3D information display, we focus on graphs     

Recursive scan-matching SLAM

This paper presents Scan-SLAM, a new generalization of simultaneous localization and mapping (SLAM). SLAM implementations based on extended Kalman filter (EKF) data fusion have traditionally relied on simple geometric models for defining landmarks. This limits EKF-SLAM to environments suited to such models and tends to discard much potentially useful data. The approach presented in this paper is a marriage of EKF-SLAM and scan correlation. Landmarks are no longer defined by analytical models; instead they are defined by templates composed of raw sensed data. These templates can be augmented as more data become available so that the landmark definition improves with time. A new generic observation model is derived that is generated by scan correlation, and this permits stochastic location estimation for landmarks with arbitrary shape within the Kalman filter framework. The statistical advantages of an EKF representation are augmented with the general applicability of scan matching. Scan matching also serves to enhance data association reliability by providing a shape metric for landmark disambiguation. Experimental results in an outdoor environment are presented which validate the algorithm.     

High Reliefs from 3D Scenes

We present a method for synthesizing high reliefs, a sculpting technique that attaches 3D objects onto a 2D surface within a limited depth range. The main challenges are the preservation of distinct scene parts by preserving depth discontinuities, the fine details of the shape, and the overall continuity of the scene. Bas relief depth compression methods such as gradient compression and depth range compression are not applicable for high relief production. Instead, our method is based on differential coordinates to bring scene elements to the relief plane while preserving depth discontinuities and surface details of the scene. We select a user‐defined number of attenuation points within the scene, attenuate these points towards the relief plane and recompute the positions of all scene elements by preserving the differential coordinates. Finally, if the desired depth range is not achieved we apply a range compression. High relief synthesis is semi‐automatic and can be controlled by user‐defined parameters to adjust the depth range, as well as the placement of the scene elements with respect to the relief plane.     

基于形变模型的多视图三维人脸重建

本文提出了基于形变模型的多视图三维人脸重建方法,将人脸形变模型与同一人脸在不同视点下的多幅图像进行匹配,从而重建出具有较强真实感的三维人脸模型。本文将对基于形变模型的多视图三维人脸重建方法进行详细的阐述,并把实验结果与单视图重建出的三维人脸模型进行了对比,从而体现出多视图重建的优势所在。     

Bayesian 3D shape from silhouettes

This paper introduces a smooth posterior density function for inferring shapes from silhouettes. Both the likelihood and the prior are modelled using kernel density functions and optimisation is performed using gradient ascent algorithms. Adding a prior allows for the recovery of concave areas of the shape that are usually lost when estimating the visual hull. This framework is also extended to use colour information when it is available in addition to the silhouettes. In these cases, the modelling not only allows for the shape to be recovered but also its colour information. Our new algorithms are assessed by reconstructing 2D shapes from 1D silhouettes and 3D faces from 2D silhouettes. Experimental results show that using the prior can assist in reconstructing concave areas and also illustrate the benefits of using colour information even when only small numbers of silhouettes are available.     

SynthText3D: synthesizing scene text images from 3D virtual worlds

With the development of deep neural networks,the demand for a significant amount of annotated training data becomes the performance bottlenecks in many fields o...