Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application ...Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application of multi-source data becomes necessary.This paper presents an evidential reasoning (ER) approach to incorporate Landsat TM imagery,altitude and slope data.Results show that multi-source data contribute to the classification accuracy achieved by the ER method,whereas play a negative role to that derived by maximum likelihood classifier (MLC).In comparison to the results derived based on TM imagery alone,the overall accuracy rate of the ER method increases by 7.66% and that of the MLC method decreases by 8.35% when all data sources (TM plus altitude and slope) are accessible.The ER method is regarded as a better approach for multi-source image classification.In addition,the method produces not only an accurate classification result,but also the uncertainty which presents the inherent difficulty in classification decisions.The uncertainty associated to the ER classification image is evaluated and proved to be useful for improved classification accuracy.展开更多
The 3D digitalization and documentation of ancient Chinese architecture is challenging because of architectural complexity and structural delicacy.To generate complete and detailed models of this architecture,it is be...The 3D digitalization and documentation of ancient Chinese architecture is challenging because of architectural complexity and structural delicacy.To generate complete and detailed models of this architecture,it is better to acquire,process,and fuse multi-source data instead of single-source data.In this paper,we describe our work on 3D digital preservation of ancient Chinese architecture based on multi source data.We first briefly introduce two surveyed ancient Chinese temples,Foguang Temple and Nanchan Temple.Then,we report the data acquisition equipment we used and the multi-source data we acquired.Finally,we provide an overview of several applications we conducted based on the acquired data,including ground and aerial image fusion,image and LiDAR(light detection and ranging)data fusion,and architectural scene surface reconstruction and semantic modeling.We believe that it is necessary to involve multi-source data for the 3D digital preservation of ancient Chinese architecture,and that the work in this paper will serve as a heuristic guideline for the related research communities.展开更多
Data diversity and abundance are essential for improving the performance and generalization of models in natural language processing and 2D vision.However,the 3D vision domain suffers from a lack of 3D data,and simply...Data diversity and abundance are essential for improving the performance and generalization of models in natural language processing and 2D vision.However,the 3D vision domain suffers from a lack of 3D data,and simply combining multiple 3D datasets for pretraining a 3D backbone does not yield significant improvement,due to the domain discrepancies among different 3D datasets that impede effective feature learning.In this work,we identify the main sources of the domain discrepancies between 3D indoor scene datasets,and propose Swin3d++,an enhanced architecture based on Swin3d for efficient pretraining on multi-source 3D point clouds.Swin3d++introduces domain-specific mechanisms to SWIN3D's modules to address domain discrepancies and enhance the network capability on multi-source pretraining.Moreover,we devise a simple source-augmentation strategy to increase the pretraining data scale and facilitate supervised pretraining.We validate the effectiveness of our design,and demonstrate that Swin3d++surpasses the state-of-the-art 3D pretraining methods on typical indoor scene understanding tasks.展开更多
皮划艇运动作为奥运会的重要比赛项目,其训练阶段目前尚未广泛应用高精度定位和地图的可视化技术。针对这一缺口,该文提出了一种国内首创的基于实景三维的皮划艇运动监控系统。该系统集成了高精度定位技术、虚拟现实技术及虚实轨迹融合...皮划艇运动作为奥运会的重要比赛项目,其训练阶段目前尚未广泛应用高精度定位和地图的可视化技术。针对这一缺口,该文提出了一种国内首创的基于实景三维的皮划艇运动监控系统。该系统集成了高精度定位技术、虚拟现实技术及虚实轨迹融合技术,为运动员和教练提供了一个直观且精确的数据分析平台。该文首先概述了系统建设的背景和重要性,然后阐述了系统的架构、主要功能以及数据库设计,最后利用Cesium三维地球引擎、ArcGIS Server地图服务器、ArcGIS API for JavaScript和WebSocket等技术进行了软件系统实现,并对关键功能的实现方法进行了说明。系统核心功能涵盖了训练场的三维可视化、场馆查询与定位、虚实轨迹数据接入、实时定位监控、轨迹回放以及数据分析等,具备高精度定位、三维实景可视以及虚实融合等独特特点。此系统的应用有利于提升皮划艇训练的效率和质量,并为相关领域研究提供有价值的参考。展开更多
基金Under the auspices of National Natural Science Foundation of China (No.40871188)Knowledge Innovation Programs of Chinese Academy of Sciences (No.INFO-115-C01-SDB4-05)
文摘Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application of multi-source data becomes necessary.This paper presents an evidential reasoning (ER) approach to incorporate Landsat TM imagery,altitude and slope data.Results show that multi-source data contribute to the classification accuracy achieved by the ER method,whereas play a negative role to that derived by maximum likelihood classifier (MLC).In comparison to the results derived based on TM imagery alone,the overall accuracy rate of the ER method increases by 7.66% and that of the MLC method decreases by 8.35% when all data sources (TM plus altitude and slope) are accessible.The ER method is regarded as a better approach for multi-source image classification.In addition,the method produces not only an accurate classification result,but also the uncertainty which presents the inherent difficulty in classification decisions.The uncertainty associated to the ER classification image is evaluated and proved to be useful for improved classification accuracy.
文摘The 3D digitalization and documentation of ancient Chinese architecture is challenging because of architectural complexity and structural delicacy.To generate complete and detailed models of this architecture,it is better to acquire,process,and fuse multi-source data instead of single-source data.In this paper,we describe our work on 3D digital preservation of ancient Chinese architecture based on multi source data.We first briefly introduce two surveyed ancient Chinese temples,Foguang Temple and Nanchan Temple.Then,we report the data acquisition equipment we used and the multi-source data we acquired.Finally,we provide an overview of several applications we conducted based on the acquired data,including ground and aerial image fusion,image and LiDAR(light detection and ranging)data fusion,and architectural scene surface reconstruction and semantic modeling.We believe that it is necessary to involve multi-source data for the 3D digital preservation of ancient Chinese architecture,and that the work in this paper will serve as a heuristic guideline for the related research communities.
文摘Data diversity and abundance are essential for improving the performance and generalization of models in natural language processing and 2D vision.However,the 3D vision domain suffers from a lack of 3D data,and simply combining multiple 3D datasets for pretraining a 3D backbone does not yield significant improvement,due to the domain discrepancies among different 3D datasets that impede effective feature learning.In this work,we identify the main sources of the domain discrepancies between 3D indoor scene datasets,and propose Swin3d++,an enhanced architecture based on Swin3d for efficient pretraining on multi-source 3D point clouds.Swin3d++introduces domain-specific mechanisms to SWIN3D's modules to address domain discrepancies and enhance the network capability on multi-source pretraining.Moreover,we devise a simple source-augmentation strategy to increase the pretraining data scale and facilitate supervised pretraining.We validate the effectiveness of our design,and demonstrate that Swin3d++surpasses the state-of-the-art 3D pretraining methods on typical indoor scene understanding tasks.
文摘皮划艇运动作为奥运会的重要比赛项目,其训练阶段目前尚未广泛应用高精度定位和地图的可视化技术。针对这一缺口,该文提出了一种国内首创的基于实景三维的皮划艇运动监控系统。该系统集成了高精度定位技术、虚拟现实技术及虚实轨迹融合技术,为运动员和教练提供了一个直观且精确的数据分析平台。该文首先概述了系统建设的背景和重要性,然后阐述了系统的架构、主要功能以及数据库设计,最后利用Cesium三维地球引擎、ArcGIS Server地图服务器、ArcGIS API for JavaScript和WebSocket等技术进行了软件系统实现,并对关键功能的实现方法进行了说明。系统核心功能涵盖了训练场的三维可视化、场馆查询与定位、虚实轨迹数据接入、实时定位监控、轨迹回放以及数据分析等,具备高精度定位、三维实景可视以及虚实融合等独特特点。此系统的应用有利于提升皮划艇训练的效率和质量,并为相关领域研究提供有价值的参考。
