检索结果-内蒙古大学图书馆

UAV swarm air combat maneuver decision-making method based on multi-agent reinforcement learning and transferring

Science China(Information Sciences) 2024年第8期67卷 49-66页

作者： Zhiqiang ZHENG Chen WEI Haibin DUAN State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical Engineering Beihang University

During short-range air combat involving unmanned aircraft vehicle(UAV) swarms, UAVs must make accurate maneuver decisions based on information from both enemy and friendly UAVs. This dual requirement of competition and cooperation presents a significant challenge in the field of unmanned air combat. In this paper, a method based on multi-agent reinforcement learning(MARL) is proposed to address this issue. An actor network containing three subnetworks that can handle different types of situational information is designed. Hence, the results from simpler one-on-one scenarios are leveraged to enhance the complex swarm air combat training process. Separate state spaces for local and global information are designed for the actor and critic networks. A detailed reward function is proposed to encourage *** prevent lazy participants in air combat, a reward assignment operation is applied to distribute these dense rewards. Simulation testing and ablation experiments demonstrate that both the transfer operation and reward assignment operation can effectively deal with the swarm air combat scenario, and reflect the effectiveness of the proposed method.

关键词： UAV swarm short-range air combat multi-agent reinforcement learning reward assignment transfer

来源：评论

学校读者我要写书评

暂无评论

Towards imbalanced motion:part-decoupling network for video portrait segmentation

引用

Science China(Information Sciences) 2024年第7期67卷 197-210页

作者： Tianshu YU Changqun XIA Jia LI State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang University Peng Cheng Laboratory

Video portrait segmentation(VPS), aiming at segmenting prominent foreground portraits from video frames, has received much attention in recent years. However, the simplicity of existing VPS datasets leads to a limitation on extensive research of the task. In this work, we propose a new intricate large-scale multi-scene video portrait segmentation dataset MVPS consisting of 101 video clips in 7 scenario categories,in which 10843 sampled frames are finely annotated at the pixel level. The dataset has diverse scenes and complicated background environments, which is the most complex dataset in VPS to our best *** the observation of a large number of videos with portraits during dataset construction, we find that due to the joint structure of the human body, the motion of portraits is part-associated, which leads to the different parts being relatively independent in motion. That is, the motion of different parts of the portraits is imbalanced. Towards this imbalance, an intuitive and reasonable idea is that different motion states in portraits can be better exploited by decoupling the portraits into parts. To achieve this, we propose a part-decoupling network(PDNet) for VPS. Specifically, an inter-frame part-discriminated attention(IPDA)module is proposed which unsupervisedly segments portrait into parts and utilizes different attentiveness on discriminative features specified to each different part. In this way, appropriate attention can be imposed on portrait parts with imbalanced motion to extract part-discriminated correlations, so that the portraits can be segmented more accurately. Experimental results demonstrate that our method achieves leading performance with the comparison to state-of-the-art methods.

关键词： video portrait segmentation imbalanced motion unsupervised part decoupling motion correlation inter-frame attention

来源：评论

学校读者我要写书评

暂无评论

Multi-granularity sequence generation for hierarchical image classification

引用

Computational Visual Media 2024年第2期10卷 243-260页

作者： Xinda Liu Lili Wang State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China Peng Cheng Laboratory Shengzhen 518000China

Hierarchical multi-granularity image classification is a challenging task that aims to tag each given image with multiple granularity labels *** methods tend to overlook that different image regions contribute differently to label prediction at different granularities,and also insufficiently consider relationships between the hierarchical multi-granularity *** introduce a sequence-to-sequence mechanism to overcome these two problems and propose a multi-granularity sequence generation(MGSG)approach for the hierarchical multi-granularity image classification ***,we introduce a transformer architecture to encode the image into visual representation ***,we traverse the taxonomic tree and organize the multi-granularity labels into sequences,and vectorize them and add positional *** proposed multi-granularity sequence generation method builds a decoder that takes visual representation sequences and semantic label embedding as inputs,and outputs the predicted multi-granularity label *** decoder models dependencies and correlations between multi-granularity labels through a masked multi-head self-attention mechanism,and relates visual information to the semantic label information through a crossmodality attention *** this way,the proposed method preserves the relationships between labels at different granularity levels and takes into account the influence of different image regions on labels with different *** on six public benchmarks qualitatively and quantitatively demonstrate the advantages of the proposed *** project is available at https://***/liuxindazz/mgs.

关键词： hierarchical multi-granularity classification vision and text transformer sequence generation fine-grained image recognition cross-modality attenti

来源：评论

学校读者我要写书评

暂无评论

Extremum seeking control for UAV close formation flight via improved pigeon-inspired optimization

引用

Science China(Technological Sciences) 2024年第2期67卷 435-448页

作者： YUAN GuangSong DUAN HaiBin State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang University(BUAA)Beijing 100083China

This paper proposes a comprehensive design scheme for the extremum seeking control(ESC)of the unmanned aerial vehicle(UAV)close formation *** proposed design scheme combines a Newton-Raphson method with an extended Kalman filter(EKF)to dynamically estimate the optimal position of the following UAV relative to the leading *** reflect the wake vortex effects reliably,the drag coefficient induced by the wake vortex is considered as a performance ***,the performance function is parameterized by the first-order and second-order terms of its Taylor series *** the excellent performance of nonlinear estimation,the EKF is used to estimate the gradient and the Hessian matrix of the parameterized performance *** output feedback of the proposed scheme is determined by iterative calculation of the Newton-Raphson *** with the traditional ESC and the classic ESC,the proposed design scheme avoids the slow continuous time integration of the *** allows a faster convergence of relative position ***,the proposed method can provide a smoother command during the seeking process as the second-order term of the performance function is taken into *** convergence analysis of the proposed design scheme is accomplished by showing that the output feedback is a supermartingale *** improve estimation performance of the EKF,a improved pigeon-inspired optimization(IPIO)is proposed to automatically tune the noise covariance *** Carlo simulations for a three-UAV close formation show that the proposed design scheme is robust to the initial position of the following UAV.

关键词： unmanned aerial vehicle close formation extremum seeking control Newton-Raphson method improved pigeon-inspired optimization

来源：评论

学校读者我要写书评

暂无评论

Multi-Scale Binocular Stereo Matching Based on Semantic Association

引用

Chinese Journal of Electronics 2024年第4期33卷 1010-1022页

作者： Jin ZHENG Botao JIANG Wei PENG Qiaohui ZHANG State Key Laboratory of Virtual Reality Techonology and Systems Beihang University School of Computer Science and Engineering Beihang University

Aiming at the low accuracy of existing binocular stereo matching and depth estimation methods, this paper proposes a multi-scale binocular stereo matching network based on semantic association. A semantic association module is designed to construct the contextual semantic association relationship among the pixels through semantic category and attention mechanism. The disparity of those regions where the disparity is easily estimated can be used to assist the disparity estimation of relatively difficult regions, so as to improve the accuracy of disparity estimation of the whole image. Simultaneously, a multi-scale cost volume computation module is proposed. Unlike the existing methods, which use a single cost volume, the proposed multi-scale cost volume computation module designs multiple cost volumes for features of different scales. The semantic association feature and multi-scale cost volume are aggregated, which fuses the high-level semantic information and the low-level local detailed information to enhance the feature representation for accurate stereo matching. We demonstrate the effectiveness of the proposed solutions on the KITTI2015 binocular stereo matching dataset, and our model achieves comparable or higher matching performance, compared to other seven classic binocular stereo matching algorithms.

关键词： Costs Accuracy Attention mechanisms Fuses Computational modeling Semantics Estimation

来源：评论

学校读者我要写书评

暂无评论

AR assistance for efficient dynamic target search

引用

Computational Visual Media 2023年第1期9卷 177-194页

作者： Zixiang Zhao Jian Wu Lili Wang State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina

When searching for a dynamic target in an unknown real world scene,search efficiency is greatly reduced if users lack information about the spatial structure of the *** target search studies,especially in robotics,focus on determining either the shortest path when the target’s position is known,or a strategy to find the target as quickly as possible when the target’s position is ***,the target’s position is often known intermittently in the real world,e.g.,in the case of using surveillance *** goal is to help user find a dynamic target efficiently in the real world when the target’s position is intermittently *** order to achieve this purpose,we have designed an AR guidance assistance system to provide optimal current directional guidance to users,based on searching a prediction *** assume that a certain number of depth cameras are fixed in a real scene to obtain dynamic target’s *** system automatically analyzes all possible meetings between the user and the target,and generates optimal directional guidance to help the user catch up with the target.A user study was used to evaluate our method,and its results showed that compared to free search and a top-view method,our method significantly improves target search efficiency.

关键词： augmented reality(AR) search guidance

来源：评论

学校读者我要写书评

暂无评论

FDCPNet:feature discrimination and context propagation network for 3D shape representation

引用

虚拟现实与智能硬件(中英文) 2025年第1期7卷 83-94页

作者： Weimin SHI Yuan XIONG Qianwen WANG Han JIANG Zhong ZHOU State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Background Three-dimensional(3D)shape representation using mesh data is essential in various applications,such as virtual reality and simulation *** methods for extracting features from mesh edges or faces struggle with complex 3D models because edge-based approaches miss global contexts and face-based methods overlook variations in adjacent areas,which affects the overall *** address these issues,we propose the Feature Discrimination and Context Propagation Network(FDCPNet),which is a novel approach that synergistically integrates local and global features in mesh *** FDCPNet is composed of two modules:(1)the Feature Discrimination Module,which employs an attention mechanism to enhance the identification of key local features,and(2)the Context Propagation Module,which enriches key local features by integrating global contextual information,thereby facilitating a more detailed and comprehensive representation of crucial areas within the mesh *** Experiments on popular datasets validated the effectiveness of FDCPNet,showing an improvement in the classification accuracy over the baseline ***,even with reduced mesh face numbers and limited training data,FDCPNet achieved promising results,demonstrating its robustness in scenarios of variable complexity.

关键词： 3D shape representation Mesh model MeshNet Feature discrimination Context propagation

来源：评论

学校读者我要写书评

暂无评论

Automatic image matting and fusing for portrait synthesis

引用

Science China(Information Sciences) 2022年第2期65卷 235-237页

作者： Zhike YI Wenfeng SONG Shuai LI Aimin HAO State Key Laboratory of Virtual Reality Technology and Systems Beihang University

We propose an automatic image matting and fusing system for portrait synthesis in this *** firstly use a face detection algorithm to determine if the input contains a ***,we use a semantic segmentation neural network to generate a trimap and feed the trimap and the portrait into the neural network to predict the alpha channel ***,the input portrait’s background is replaced with the given background via an image synthesis algorithm to obtain the synthesized portrait.

关键词： Neural Network Automatic Image Matting Image Fusion Deep Learning Gradient Domain

来源：评论

学校读者我要写书评

暂无评论

Skinned Motion Retargeting with Preservation of Body Part Relationships

引用

IEEE Transactions on Visualization and Computer Graphics 2024年 PP卷 1-13页

作者： Zhang, Jia-Qi Wang, Miao Zhang, Fu-Cheng Zhang, Fang-Lue State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China School of Engineering and Computer Science Victoria University of Wellington New Zealand

Motion retargeting is an active research area in computer graphics and animation, allowing for the transfer of motion from one character to another, thereby creating diverse animated character data. While this technology has numerous applications in animation, games, and movies, current methods often produce unnatural or semantically inconsistent motion when applied to characters with different shapes or joint counts. This is primarily due to a lack of consideration for the geometric and spatial relationships between the body parts of the source and target characters. To tackle this challenge, we introduce a novel spatially-preserving Skinned Motion Retargeting Network (SMRNet) capable of handling motion retargeting for characters with varying shapes and skeletal structures while maintaining semantic consistency. By learning a hybrid representation of the character's skeleton and shape in a rest pose, SMRNet transfers the rotation and root joint position of the source character's motion to the target character through embedded rest pose feature alignment. Additionally, it incorporates a differentiable loss function to further preserve the spatial consistency of body parts between the source and target. Comprehensive quantitative and qualitative evaluations demonstrate the superiority of our approach over existing alternatives, particularly in preserving spatial relationships more effectively IEEE

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Web-based mixed reality video fusion with remote rendering

引用

virtual reality & Intelligent Hardware 2023年第2期5卷 188-199页

作者： Qiang ZHOU Zhong ZHOU State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China

Background Mixed reality(MR)video fusion systems merge video imagery with 3D scenes to make the scene more realistic and help users understand the video content and temporal–spatial correlation between them,reducing the user′s cognitive *** video fusion are used in various applications;however,video fusion systems require powerful client machines because video streaming delivery,stitching,and rendering are computationally ***,huge bandwidth usage is another critical factor that affects the scalability of video-fusion *** Our framework proposes a fusion method for dynamically projecting video images into 3D models as *** Several experiments on different metrics demonstrate the effectiveness of the proposed *** The framework proposed in this study can overcome client limitations by utilizing remote ***,the framework we built is based on ***,the user can test the MR video fusion system with a laptop or tablet without installing any additional plug-ins or application programs.

关键词： Mixed reality Video fusion WebRTC Remote rendering

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：