检索结果-内蒙古大学图书馆

Learning Multi-Modal Scale-Aware Attentions for Efficient and Robust Road Segmentation

无人系统（英文） 2024年第2期12卷 201-213页

作者： Yunjiao Zhou Jianfei Yang Haozhi Cao Zhaoyang Zeng Han Zou Lihua Xie School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore Computer Vision and Robot Research Center International Digital Economy AcademyShenzhenGuangdongP.R.China

Road segmentation is essential to unmanned systems,contributing to road perception and navigation in the field of autonomous *** multi-modal road segmentation methods have shown promising results by leveraging the complementary data of RGB and Depth to provide robust 3D geometry information,existing methods suffer from severe efficiency problems that hinder their practical appli-cation in autonomous *** direct concatenation of multi-modal features with a densely-connected network leads to increased semantic gaps among modalities and scales,causing high computational and time *** address these issues,we propose a Multi-modal Scale-aware Attention Network(MSAN)to fuse RGB and Depth data effectively via a novel transformer-based cross-attention module,namely Multi-modal Scare-aware Transformer(MST),which fuses RGB-D features from a global perspective across multiple *** better consolidate different scales of features,we further propose a Scale-aware Attention Module(SAM)that captures channel-wise attention efficiently for cross-scale *** two attention-based modules explore the complementarity of modalities and scales,narrowing the gaps and avoiding complex structures for road *** experiments demonstrate MSAN achieves competitive performance at a low computational cost,suitable for real-time implementation on edge-devices in autonomous driving systems.

关键词： Autonomous driving road segmentation multi-modal fusion cross attention scale-aware fusion real-time application

来源：评论

学校读者我要写书评

暂无评论

Towards Source-Free Domain Adaptive Semantic Segmentation Via Importance-Aware and Prototype-Contrast Learning

IEEE Transactions on Intelligent Vehicles

引用

IEEE Transactions on Intelligent Vehicles 2024年 1-13页

作者： Cao, Yihong Zhang, Hui Lu, Xiao Xiao, Zheng Yang, Kailun Wang, Yaonan College of Computer Science and Electronic Engineering Hunan University Changsha China National Engineering Research Center of Robot Vision Perception and Control Technology School of Robotics Hunan University Changsha China College of Engineering and Design Hunan Normal University Changsha China

Domain adaptive semantic segmentation enables robust pixel- wise understanding in real-world driving scenes. Source-free domain adaptation, as a more practical technique, addresses the concerns of data privacy and storage limitations in typical unsupervised domain adaptation methods, making it especially relevant in the context of intelligent vehicles. It utilizes a well-trained source model and unlabeled target data to achieve adaptation in the target domain. However, in the absence of source data and target labels, current solutions cannot sufficiently reduce the impact of domain shift and fully leverage the information from the target data. In this paper, we propose an end-to-end source-free domain adaptation semantic segmentation method via Importance-Aware and Prototype-Contrast (IAPC) learning. The proposed IAPC framework effectively extracts domain-invariant knowledge from the well-trained source model and learns domain-specific knowledge from the unlabeled target domain. Specifically, considering the problem of domain shift in the prediction of the target domain by the source model, we put forward an importance-aware mechanism for the biased target prediction probability distribution to extract domain-invariant knowledge from the source model. We further introduce a prototype-contrast strategy, which includes a prototype-symmetric cross-entropy loss and a prototype-enhanced cross-entropy loss, to learn target intra-domain knowledge without relying on labels. A comprehensive variety of experiments on two domain adaptive semantic segmentation benchmarks demonstrates that the proposed end-to-end IAPC solution outperforms existing state-of-the-art methods. The source code is publicly available at https://***/yihong-97/Source-free-IAPC. IEEE

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Towards Source-free Domain Adaptive Semantic Segmentation via Importance-aware and Prototype-contrast Learning

arXiv

引用

arXiv 2023年

作者： Cao, Yihong Zhang, Hui Lu, Xiao Xiao, Zheng Yang, Kailun Wang, Yaonan College of Computer Science and Electronic Engineering Hunan University Changsha410082 China National Engineering Research Center of Robot Vision Perception and Control Technology School of Robotics Hunan University Changsha410082 China College of Engineering and Design Hunan Normal University Changsha410082 China

Domain adaptive semantic segmentation enables robust pixel-wise understanding in real-world driving scenes. Source-free domain adaptation, as a more practical technique, addresses the concerns of data privacy and storage limitations in typical unsupervised domain adaptation methods, making it especially relevant in the context of intelligent vehicles. It utilizes a well-trained source model and unlabeled target data to achieve adaptation in the target domain. However, in the absence of source data and target labels, current solutions cannot sufficiently reduce the impact of domain shift and fully leverage the information from the target data. In this paper, we propose an end-to-end source-free domain adaptation semantic segmentation method via Importance-Aware and Prototype-Contrast (IAPC) learning. The proposed IAPC framework effectively extracts domain-invariant knowledge from the well-trained source model and learns domain-specific knowledge from the unlabeled target domain. Specifically, considering the problem of domain shift in the prediction of the target domain by the source model, we put forward an importance-aware mechanism for the biased target prediction probability distribution to extract domain-invariant knowledge from the source model. We further introduce a prototype-contrast strategy, which includes a prototype-symmetric cross-entropy loss and a prototype-enhanced cross-entropy loss, to learn target intra-domain knowledge without relying on labels. A comprehensive variety of experiments on two domain adaptive semantic segmentation benchmarks demonstrates that the proposed end-to-end IAPC solution outperforms existing state-of-the-art methods. The source code is publicly available at https://***/yihong-97/Source-free-IAPC. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Fast perception, planning, and execution for a robotic butler: Wheeled humanoid m-hubo

arXiv

引用

arXiv 2020年

作者： Lee, Moonyoung Heo, Yujin Park, Jinyong Yang, Hyun-Dae Jang, Ho-Deok Benz, Philipp Park, Hyunsub Kweon, In So Oh, Jun-Ho Humanoid Robot Research Center Department of Mechanical Engineering Korea Advanced Institute of Science and Technology 291 Daehak-ro Yuseong-gu Daejeon34141 Korea Republic of Robotics and Computer Vision Laboratory Department of Electrical Engineering Korea Advanced Institute of Science and Technology 291 Daehak-ro Yuseong-gu Daejeon34141 Korea Republic of

As the aging population grows at a rapid rate, there is an ever growing need for service robot platforms that can provide daily assistance at practical speed with reliable performance. In order to assist with daily tasks such as fetching a beverage, a service robot must be able to perceive its environment and generate corresponding motion trajectories. This becomes a challenging and computationally complex problem when the environment is unknown and thus the path planner must sample numerous trajectories that often are sub-optimal, extending the execution time. To address this issue, we propose a unique strategy of integrating a 3D object detection pipeline with a kinematically optimal manipulation planner to significantly increase speed performance at runtime. In addition, we develop a new robotic butler system for a wheeled humanoid that is capable of fetching requested objects at 24% of the speed a human needs to fulfill the same task. The proposed system was evaluated and demonstrated in a real-world environment setup as well as in public exhibition. Copyright © 2020, The Authors. All rights reserved.

关键词： Mobile robots

来源：评论

学校读者我要写书评

暂无评论

An overview of contest on Semantic Description of Human Activities (SDHA) 2010

An overview of contest on Semantic Description of Human Acti...

引用

20th International Conference on Pattern Recognition, ICPR 2010

作者： Ryoo, M.S. Chen, Chia-Chih Aggarwal, J.K. Roy-Chowdhury, Amit Computer and Vision Research Center University of Texas Austin TX United States Robot/Cognition Research Department ETRI Korea Republic of Video Computing Group Dept. of EE University of California Riverside CA United States

ISBN: (纸本)3642177107

This paper summarizes results of the 1st Contest on Semantic Description of Human Activities (SDHA), in conjunction with ICPR 2010. SDHA 2010 consists of three types of challenges, High-level Human Interaction Recognition Challenge, Aerial View Activity Classification Challenge, and Wide-Area Activity Search and Recognition Challenge. The challenges are designed to encourage participants to test existing methodologies and develop new approaches for complex human activity recognition scenarios in realistic environments. We introduce three new public datasets through these challenges, and discuss results of the state-of-the-art activity recognition systems designed and implemented by the contestants. A methodology using a spatio-temporal voting [19] successfully classified segmented videos in the UT-Interaction datasets, but had a difficulty correctly localizing activities from continuous videos. Both the method using local features [10] and the HMM based method [18] recognized actions from low-resolution videos (i.e. UT-Tower dataset) successfully. We compare their results in this paper. © 2010 Springer-Verlag.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

View independent recognition of human-vehicle interactions using 3-D models

View independent recognition of human-vehicle interactions u...

引用

2009 Workshop on Motion and Video Computing, WMVC '09

作者： Lee, Jong T. Ryoo, M.S. Aggarwal, J.K. Computer and Vision Research Center Department of ECE University of Texas Austin TX United States Robot Research Department Electronics and Telecommunications Research Institute Korea Republic of

ISBN: (纸本)9781424455003

Recognition of human-vehicle interactions is a challenging problem. The occlusion by vehicles and motion of humans contribute to the difficulty. In this paper, we present a novel approach for the view independent recognition of human-vehicle interactions. The shape based matching of synthetic 3-D vehicle models is used for accurate localization of vehicles and for the specification of regions-ofinterest (e.g. doors). In the proposed method, the system transforms the optical flow field based on the position of doors and the direction of a vehicle. This enables the system to extract view-independent features. Histogram of oriented optical flow (HOOF) and histogram of oriented gradient (HOG) characterize the optical flow and gradient, respectively. A support vector machine (SVM) classifier is trained for these view-independent features. Consequently, the system recognizes the interactions of a person entering a vehicle and getting out of a vehicle. Our method is applied to a dataset of human-vehicle interactions taken from 8 different viewpoints, composed of 120 video clips. The experimental results show that the system recognizes sequences of complex human-vehicle interactions with a high recognition rate of 86 %. ©2009 IEEE.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

View independent recognition of human-vehicle interactions using 3-D models

View independent recognition of human-vehicle interactions u...

引用

Workshop on Motion and Video Computing

作者： Jong T. Lee M. S. Ryoo J. K. Aggarwal Computer & Vision Research Center / Department of ECE University of Texas Austin USA Robot Research Department Electronics and Telecommunications Research Institute South Korea

ISBN: (纸本)9781424455003

Recognition of human-vehicle interactions is a challenging problem. The occlusion by vehicles and motion of humans contribute to the difficulty. In this paper, we present a novel approach for the view independent recognition of human-vehicle interactions. The shape based matching of synthetic 3D vehicle models is used for accurate localization of vehicles and for the specification of regions-of-interest (e.g. doors). In the proposed method, the system transforms the optical flow field based on the position of doors and the direction of a vehicle. This enables the system to extract view-independent features. Histogram of oriented optical flow (HOOF) and histogram of oriented gradient (HOG) characterize the optical flow and gradient, respectively. A support vector machine (SVM) classifier is trained for these view-independent features. Consequently, the system recognizes the interactions of a person entering a vehicle and getting out of a vehicle. Our method is applied to a dataset of human-vehicle interactions taken from 8 different viewpoints, composed of 120 video clips. The experimental results show that the system recognizes sequences of complex human-vehicle interactions with a high recognition rate of 86%.

关键词： Humans Shape Image motion analysis Feature extraction Support vector machines Support vector machine classification Vehicle detection computer vision Histograms Cameras

来源：评论

学校读者我要写书评

暂无评论

robotIC AND ARTIFICIAL-INTELLIGENCE SYSTEMS FOR THE NAVAL OPERATIONAL ENVIRONMENT

引用

NAVAL ENGINEERS JOURNAL 1987年第4期99卷 74-86页

作者： HOGGE, SM The author earned her bachelor's of science degree in industrial engineering and operations research from Virginia Polytechnic Institute and State University. While at Virginia Tech she worked in the Robotics Laboratory supporting robotics research sponsored by the National Bureau of Standards. She completed her master's of science in computer science at The Johns Hopkins University. Until this past March Miss Hogge worked at the Naval Surface Weapons Center in Silver Spring Maryland. Her duties included the application of robotics and artificial intelligence to explosive ordnance disassembly mobile robotics remote controlled fire fighting vehicles human factors expert systems computer enhanced decision-making aids and hardware security. She published a two-volume study discussing shipboard operational applications of robotics and AI. In addition her publications include nine recent journal articles on robotics and computer security. Miss Hogge is currently employed with Automaker Inc. in Houston Texas. Her current role is manager of all government related robotic operations and vision systems. Miss Hogge's projects at Automaker include: an explosive ordnance disassembly gantry robot system a vision inspection system to examine bearings 3-part camouflage spray painting an investigation of the use of robotic welding in Navy shipyards and rework facilities and epoxy spray painting of missile radomes.

Due to demographical factors, there will be a 25% decline in the national labor pool of eligible 17 to 21 year old men by 1992. As the Navy faces fierce competition with other services and private industry for the dwindling personnel resources of the nation, efforts must be made to consider automating certain tasks, especially those that are hazardous, boring, and labor intensive onboard ships at sea. The Surface Ship Continuing Concept Formulation (CONFORM) Program (SEA-5014) sponsored the Naval Surface Weapons center's robotics Laboratory to identify potential applications of robotic and artificial intelligence systems to operation and mission activities for shipboard use. The results of the investigation concerning applications of robotics to automate the aforementioned tasks are presented. Changes in current manning levels for selected tasks and ship classes, i.e., CVs, CVNs, LPDs, LPNs, and auxiliaries are examined. Future ship designs incorporating robotics, such as the advance based repair (ABR) ship are discussed. Twenty-four applications were cited in the study which include a remote controlled vehicle for flight deck operations, limited tasks in biological, chemical, and radiation environments, computer aided command decision aids, ordnance handling, undersea search, recovery, and salvage, and ventilation duct cleaning. Four of the applications and their subsequent hardware fruition will be discussed.

关键词： robotICS

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：