Semi-Direct Monocular Visual-Inertial Odometry Using Point and Line Features for IoV

The precise measuring of vehicle location has been a critical task in enhancing the autonomous driving in terms of intelligent decision making and safe transportation. Internet of Vehicles ( IoV ) is an important infrastructure in support of autonomous driving, allowing real-time road information exchanging and sharing for localizing vehicles. Global positioning System ( GPS ) is widely used in the traditional IoV system. GPS is unable to meet the key application requirements of autonomous driving due to meter level error and signal deterioration. In this article, we propose a novel solution, named Semi-Direct Monocular Visual-Inertial Odometry using Point and Line Features ( SDMPL-VIO ) for precise vehicle localization. Our SDMPL-VIO model takes advantage of a low-cost Inertial Measurement Unit ( IMU ) and monocular camera, using them as the sensor to acquire the surrounding environmental information. Visual-Inertial Odometry ( VIO ), taking into account both point and line features, is proposed, which is able to deal with both weak texture and dynamic environment. We use a semi-direct method to deal with keyframes and non-keyframes, respectively. Dual sliding window mechanisms can effectively fuse point-line and IMU information. To evaluate our SDMPL-VIO system model, we conduct extensive experiments on both an indoor dataset (i.e., EuRoC) and an outdoor dataset (i.e., KITTI) from the real-world applications, respectively. The experimental results show that the accuracy of SDMPL-VIO proposed by us is better than the mainstream VIO system at present. Especially in the weak texture of the datasets, fast-moving datasets, and other challenging datasets, SDMPL-VIO has a relatively high robustness.

A New Visual Inertial Simultaneous Localization and Mapping (SLAM) Algorithm Based on Point and Line Features

In view of traditional point-line feature visual inertial simultaneous localization and mapping (SLAM) system, which has weak performance in accuracy so that it cannot be processed in real time under the condition of weak indoor texture and light and shade change, this paper proposes an inertial SLAM method based on point-line vision for indoor weak texture and illumination. Firstly, based on Bilateral Filtering, we apply the Speeded Up Robust Features (SURF) point feature extraction and Fast Nearest neighbor (FLANN) algorithms to improve the robustness of point feature extraction result. Secondly, we establish a minimum density threshold and length suppression parameter selection strategy of line feature, and take the geometric constraint line feature matching into consideration to improve the efficiency of processing line feature. And the parameters and biases of visual inertia are initialized based on maximum posterior estimation method. Finally, the simulation experiments are compared with the traditional tightly-coupled monocular visual–inertial odometry using point and line features (PL-VIO) algorithm. The simulation results demonstrate that the proposed an inertial SLAM method based on point-line vision for indoor weak texture and illumination can be effectively operated in real time, and its positioning accuracy is 22% higher on average and 40% higher in the scenario that illumination changes and blurred image.

The Interpretation of Graphical Features Applied to Mapping SWOT by the Architecture Students in the Design Studio

The purpose of this study is to gain an understanding of how the architecture students deploy a range of graphical features to visualize SWOT, standing for Strengths, Weaknesses, Opportunities, and Threats. Architectural design studios provide students with a range of analytical techniques, and SWOT analysis is considered to be useful and effective, particularly at urban-scale design projects. However, it is a text-based framework and needs to be converted to thematic analysis maps across architecture and design fields. The main issue is that the determining factors affecting the way in which students choose graphical features to map the outputs of SWOT analysis is unclear at architectural design studios. The research employed qualitative methods, specifically observation, focus group, and graphical analysis, to examine SWOT maps produced by the architecture students. The findings demonstrated that the selection of graphical features in the process of producing SWOT analysis maps are dependent on scale of study (macro, meso, and micro), as well as location, spatial connection, and size of elements derived from SWOT matrix. For instance, lines and planes were most frequent features at macro level while the variety of symbols remarkably increased at micro level. In conclusion, the students personalized the process of mapping, meaning that they applied point, line, plane (shape), color, texture, and typography in several different ways. Therefore, SWOT analysis not only help architecture students to better understand the problems of their design projects, organize and consolidate information, and visualize opportunities and constraints, but could lead to the representation of realistic solutions in an innovative way.

Automatic, Multiview, Coplanar Extraction for CityGML Building Model Texture Mapping

Most 3D CityGML building models in street-view maps (e.g., Google, Baidu) lack texture information, which is generally used to reconstruct real-scene 3D models by photogrammetric techniques, such as unmanned aerial vehicle (UAV) mapping. However, due to its simplified building model and inaccurate location information, the commonly used photogrammetric method using a single data source cannot satisfy the requirement of texture mapping for the CityGML building model. Furthermore, a single data source usually suffers from several problems, such as object occlusion. We proposed a novel approach to achieve CityGML building model texture mapping by multiview coplanar extraction from UAV remotely sensed or terrestrial images to alleviate these problems. We utilized a deep convolutional neural network to filter out object occlusion (e.g., pedestrians, vehicles, and trees) and obtain building-texture distribution. Point-line-based features are extracted to characterize multiview coplanar textures in 2D space under the constraint of a homography matrix, and geometric topology is subsequently conducted to optimize the boundary of textures by using a strategy combining Hough-transform and iterative least-squares methods. Experimental results show that the proposed approach enables texture mapping for building façades to use 2D terrestrial images without the requirement of exterior orientation information; that is, different from the photogrammetric method, a collinear equation is not an essential part to capture texture information. In addition, the proposed approach can significantly eliminate blurred and distorted textures of building models, so it is suitable for automatic and rapid texture updates.

Determining the features on the image of Satellite Sentinel-2 with different resolution and comparing them with images of Satellite Sentinel-1

Land cover-land use (LCLU) classification tasks can take advantage of the fusion of radar and optical remote sensing data, leading generally to increase mapping accuracy. Here we propose a methodological approach to fuse information from the new European Space Sentinel-2 imagery for accurate land cover mapping of a portion of the region, Baghdad. I First step Download the Sentinel 2 image in its correct geographic location, then take a 10-meter, 20 meter and 60 meter resolution images then drawn point, line and polygon feature of each resolution image the discuss the difference between them The aim of this study was to discuss which resolution gives better accuracy. as the difference between the features, by redusing the resolution, it will be made difficulty in identifying the features. The landmarks appear clearly as the image resolution increases, so the features are clearer in the image with a resolution of 10 meters than the image with a resolution of 20 meters and 60 meters. Also, the images of the Sentinel-2 are clearer, and dealing with them is much easier than the images of the Sentinel-1.

Sonoric as a Compositional Technique the Attempt of Critical Analysis

Relevance of the study. Sonoric is a widespread definition in Post-Soviet countries musicology. However, it is the only one in the system of contemporary compositional techniques that does not have English analogue. This fact conditioned to a number of questions related to this technique: what English terminology should be used as an analogue of sonoric or sonoristic? Why is there no such compositional technique as sonoric in European (with the exception of Poland) and American musicology? Is sonoric a compositional technique? The actualization of these issues makes it possible to solve both terminological problems and partially approach to the creation of a complete theory of contemporary composition techniques. The purpose of the study is to attempt to identify the structural core of sonoric as a compositional technique, the parameter (or parameters) of tone or noise material, for which organization it is responsible. Methods. This article is based on the method of systemic analysis of phenomena, general methods of theoretical research (analysis of a term, its semantic boundaries, correlation with other concepts), as well as specific musicological methods of a musical text analyzing. The results and conclusions. The authors of the theory of the sonoric compositional technique (Yu. Kholopov and A. Maklygin) suggest its use both in a general (a certain quality of concords) and in a narrow sense (a compositional technique that operates with timbre mass). In the process of a critical analysis of the concept of sonoric, it was noted that there are no precise criteria for distinguishing between the sound phenomena described by sonoric. Its methodological underpinning is based more on the elements of psychoacoustics and the theory of perception (without the direct use of the methods of these sciences) than on the theory of music. This thesis is proved by comparing the concepts of sonorically colored harmony and sonoric harmony. Postulating a reliance on synesthesia, the sonoric proposes to use a set of subjective associations to describe a sound phenomenon, relying on imaginative rather than technological characteristics. The analysis of sonoric texture types showed that point, line, spot, stripe, etc. are not original ways of tone and noise sounds organization, but are based on various combinations of pointillistic, cluster, polyphonic, micropolyphonic tools. Based on this conclusion, the idea that sonoric formations are not technically unique is formed. Such sonoric texture types are created by using a certain set of methods typical for various compositional techniques.

Morphometric analysis of Rasyan valley basin - A case study in the Republic of Yemen, using Remote Sensing and GIS techniques

Remote Sensing and GIS has given more importance for investigation of the geomorphological features based on the morphometric analysis duo to the diversity of data information by using digital map characters which help in moderating of data base information to get a different data like distance, area, point, line, polygon and qualitative data. This has decreased the errors which resulted by manual map sources. The main aim of this paper is the study of a morphometric analysis and characteristics of river basin area, basin shape, length, width and the ratio of length to the width, the ratio of rotation and circularity of the basin. It is also a study of relief characteristic, like slope and basin texture hypsometric curve. And also a study of drainage network characteristic like streams, stream order, length, drainage density, turn ratio, bifurcation ratio, weighted bifurcation ratio, type of drainage, and the relationship between all variables that mentioned above with rock types and structural movements of internal and external factors which are represented by relief, climate, soil, type of vegetation along with the human impact on the other hand. Results have been discussed for Rasyan valley basin in the Republic of Yemen using Landsat data.

Generalizing the Algebra of Throws to Rank-3 Matroids

<p>The algebra of throws is a geometric construction which reveals the underlying algebraic operations of addition and multiplication in a projective plane. In Desarguesian projective planes, the algebra of throws is a well-defined, commutative and associative binary operation. However, when we consider an analogous operation in a more general point-line configuration that comes from rank-3 matroids, none of these properties are guaranteed. We construct lists of forbidden configurations which give polynomial time checks for certain properties. Using these forbidden configurations, we can check whether a configuration has a group structure under this analogous operation. We look at the properties of configurations with such a group structure, and discuss their connection to the jointless Dowling geometries.</p>

Generalizing the Algebra of Throws to Rank-3 Matroids

<p>The algebra of throws is a geometric construction which reveals the underlying algebraic operations of addition and multiplication in a projective plane. In Desarguesian projective planes, the algebra of throws is a well-defined, commutative and associative binary operation. However, when we consider an analogous operation in a more general point-line configuration that comes from rank-3 matroids, none of these properties are guaranteed. We construct lists of forbidden configurations which give polynomial time checks for certain properties. Using these forbidden configurations, we can check whether a configuration has a group structure under this analogous operation. We look at the properties of configurations with such a group structure, and discuss their connection to the jointless Dowling geometries.</p>