Geographic,Geometrical and Semantic Reconstruction of Urban Scene from High Resolution Oblique Aerial Images

An effective approach is proposed for 3D urban scene reconstruction in the form of point cloud with semantic labeling. Starting from high resolution oblique aerial images,our approach proceeds through three main stages: geographic reconstruction, geometrical reconstruction and semantic reconstruction. The absolute position and orientation of all the cameras relative to the real world are recovered in the geographic reconstruction stage. Then, in the geometrical reconstruction stage,an improved multi-view stereo matching method is employed to produce 3D dense points with color and normal information by taking into account the prior knowledge of aerial imagery.Finally the point cloud is classified into three classes(building,vegetation, and ground) by a rule-based hierarchical approach in the semantic reconstruction step. Experiments on complex urban scene show that our proposed 3-stage approach could generate reasonable reconstruction result robustly and efficiently.By comparing our final semantic reconstruction result with the manually labeled ground truth, classification accuracies from86.75% to 93.02% are obtained.

Exploiting SAR visual semantics in Tomo SAR for 3D modeling of buildings

Recently a new paradigm is emerging in synthetic aperture radar(SAR)three-dimensional(3D)imaging technology where the imaging performance is enhanced by exploiting SAR visual semantics.Here by“SAR visual semantics”,we mean primarily the scene conceptual structural information extracted directly from SAR images.Under this paradigm,a paramount open problem lies in what and how the SAR visual semantics could be extracted and used at different levels associated with different structural information.This work is a tentative attempt to tackle the above what-and-how problem,and it mainly consists of the following two parts.The first part is a sketchy description of how three-level(low,middle,and high)SAR visual semantics could be extracted and used in SAR Tomography(TomoSAR),including an extension of SAR visual semantics analysis(e.g.,facades and roofs)to sparse 3D points initially recovered via traditional TomoSAR methods.The second part is a case study on two open source TomoSAR datasets to illustrate and validate the effectiveness and efficiency of SAR visual semantics exploitation in TomoSAR for box-like 3D building modeling.Due to the space limit,only main steps of the involved methods are reported,and we hope,such neglects of technical details will not severely compromise the underlying key concepts and ideas.

Design and experimental validation of event-triggered multi-vehicle cooperation in conflicting scenarios

Platoon control is widely studied for coordinating connected and automated vehicles(CAVs)on highways due to its potential for improving traffic throughput and road safety.Inspired by platoon control,the cooperation of multiple CAVs in conflicting scenarios can be greatly simplified by virtual platooning.Vehicle-to-vehicle communication is an essential ingredient in virtual platoon systems.Massive data transmission with limited communication resources incurs inevitable imperfections such as transmission delay and dropped packets.As a result,unnecessary transmission needs to be avoided to establish a reliable wireless network.To this end,an event-triggered robust control method is developed to reduce the use of communication resources while ensuring the stability of the virtual platoon system with time-varying uncertainty.The uniform boundedness,uniform ultimate boundedness,and string stability of the closed-loop system are analytically proved.As for the triggering condition,the uncertainty of the boundary information is considered,so that the threshold can be estimated more reasonably.Simulation and experimental results verify that the proposed method can greatly reduce data transmission while creating multi-vehicle cooperation.The threshold affects the tracking ability and communication burden,and hence an optimization framework for choosing the threshold is worth exploring in future research.

A Brief Introduction of the Achievements of Key Project Image-based Modeling and Rendering for Virtual Reality Applications

1. Background The virtual reality （VR） technology is now at the frontier of modern information science. VR is based on computer graphics, computer vision, and other fresh air topics in today＇s computer technology. Nowadays the VR technology has been applied successfully in variety of fields such as military simulation, industry, medical training and visualization, environment protection and entertainment.