Synthetic Environment Data Research Articles

Relative Camera Pose Estimation using Synthetic Data with Domain Adaptation via Cycle-Consistent Adversarial Networks

Learning-based visual localization has become prospective over the past decades. Since ground truth pose labels are difficult to obtain, recent methods try to learn pose estimation networks using pixel-perfect synthetic data. However, this also introduces the problem of domain bias. In this paper, we first build a Tuebingen Buildings dataset of RGB images collected by a drone in urban scenes and create a 3D model for each scene. A large number of synthetic images are generated based on these 3D models. We take advantage of image style transfer and cycle-consistent adversarial training to predict the relative camera poses of image pairs based on training over synthetic environment data. We propose a relative camera pose estimation approach to solve the continuous localization problem for autonomous navigation of unmanned systems. Unlike those existing learning-based camera pose estimation methods that train and test in a single scene, our approach successfully estimates the relative camera poses of multiple city locations with a single trained model. We use the Tuebingen Buildings and the Cambridge Landmarks datasets to evaluate the performance of our approach in a single scene and across-scenes. For each dataset, we compare the performance between real images and synthetic images trained models. We also test our model in the indoor dataset 7Scenes to demonstrate its generalization ability.

Overview of the OGC CDB Standard for 3D Synthetic Environment Modeling and Simulation

Recent advances in sensor and platform technologies, such as satellite systems, unmanned aerial vehicles (UAV), manned aerial platforms, and ground-based sensor networks have resulted in massive volumes of data being produced and collected about the earth. Processing, managing, and analyzing these data is one of the main challenges in 3D synthetic representation used in modeling and simulation (M&S) of the natural environment. M&S devices, such as flight simulators, traditionally require a variety of different databases to provide a synthetic representation of the world. M&S often requires integration of data from a variety of sources stored in different formats. Thus, for simulation of a complex synthetic environment, such as a 3D terrain model, tackling interoperability among its components (geospatial data, natural and man-made objects, dynamic and static models) is a critical challenge. Conventional approaches used local proprietary data models and formats. These approaches often lacked interoperability and created silos of content within the simulation community. Therefore, open geospatial standards are increasingly perceived as a means to promote interoperability and reusability for 3D M&S. In this paper, the Open Geospatial Consortium (OGC) CDB Standard is introduced. “CDB” originally referred to Common DataBase, which is currently considered as a name with no abbreviation in the OGC community. The OGC CDB is an international standard for structuring, modeling, and storing geospatial information required in high-performance modeling and simulation applications. CDB defines the core conceptual models, use cases, requirements, and specifications for employing geospatial data in 3D M&S. The main features of the OGC CDB Standard are described as the run-time performance, full plug-and-play interoperable geospatial data store, usefulness in 3D and dynamic simulation environment, ability to integrate proprietary and open-source data formats. Furthermore, compatibility with the OGC standards baseline reduces the complexity of discovering, transforming, and streaming geospatial data into the synthetic environment and makes them more widely acceptable to major geospatial data/software producers. This paper includes an overview of OGC CDB version 1.0, which defines a conceptual model and file structure for the storage, access, and modification of a multi-resolution 3D synthetic environment data store. Finally, this paper presents a perspective of future versions of the OGC CDB and what the steps are for humanizing the OGC CDB standard with the other OGC/ISO standards baseline.

Visualization of the Synthetic Environment Data Representation & Interchange Specification data for verifying large-scale synthetic environment data

The need for reusing synthetic environment data that are employed in the field of modeling and simulation has recently been rising. SEDRIS (Synthetic Environment Data Representation & Interchange Specification) is a standard to exchange synthetic environment data, and is the specification utilized in various military simulations of the Pentagon for representing and exchanging three-dimensional data. SEDRIS represents environmental areas based on a data model; it can represent wind speed, wind directions, weather changes, and the information of buildings, as well as terrain data. In some situations, however, the synthetic environment data stored in SEDRIS format should be converted to various visualization formats. Firstly, because SEDRIS is a form of a super-set, it is necessary to verify whether large-scale SEDRIS files are stored successfully through visualization. In addition, the synthetic environment data should be visualized in some visualization programs for the simulation results to provide an immersive and realistic sense. In this study, we suggest several methods for visualizing synthetic environmental data stored in the SEDRIS format. We developed the converters for converting SEDRIS to the several visualization formats and developed the direct visualization programs using an open-source visualization engine. These results allow us to visualize the stored SEDRIS file and to verify whether the saving stage with native data is performed normally or not.

SEDRIS 합성 환경 데이터 가시화를 위한 변환기 개발

The need for reusing synthetic environment data that are employed in the field of modeling and simulation has recently been rising. SEDRIS (Synthetic Environment Data Representation & Interchange Specification) is a standard to exchange synthetic environment data, and is the specification utilized in various military simulations of the Pentagon for representing and exchanging 3D data. SEDRIS represents environmental areas based on a data model; it can represent wind speed, wind directions, weather changes, the information of buildings, as well as terrain data. In some situations, however, the synthetic environment data stored in SEDRIS format should be converted to various visualization formats. First, because SEDRIS is a form of a super-set, it is necessary to verify whether large scale SEDRIS files are stored successfully through visualization. Second, the synthetic environment data should be visualized in some visualization programs for the simulation results to provide an immersive and realistic sense. In this study, we have developed converters for converting SEDRIS data to various visualization formats and visualized the converted results.