检索结果-内蒙古大学图书馆

2012 IEEE/RSJ International Conference on intelligent Robots and Systems

作者： Jürgen Sturm Nikolas Engelhard Felix Endres Wolfram Burgard Daniel Cremers Computer Vision Group Computer Science Department Technical University of Munich Germany Autonomous Intelligent Systems Laboratory Computer Science Department University of Freiburg Germany

ISBN: (纸本)9781467317375

In this paper, we present a novel benchmark for the evaluation of RGB-D SLAM systems. We recorded a large set of image sequences from a Microsoft Kinect with highly accurate and time-synchronized ground truth camera poses from a motion capture system. The sequences contain both the color and depth images in full sensor resolution (640 × 480) at video frame rate (30 Hz). The ground-truth trajectory was obtained from a motion-capture system with eight high-speed tracking cameras (100 Hz). The dataset consists of 39 sequences that were recorded in an office environment and an industrial hall. The dataset covers a large variety of scenes and camera motions. We provide sequences for debugging with slow motions as well as longer trajectories with and without loop closures. Most sequences were recorded from a handheld Kinect with unconstrained 6-DOF motions but we also provide sequences from a Kinect mounted on a Pioneer 3 robot that was manually navigated through a cluttered indoor environment. To stimulate the comparison of different approaches, we provide automatic evaluation tools both for the evaluation of drift of visual odometry systems and the global pose error of SLAM systems. The benchmark website [1] contains all data, detailed descriptions of the scenes, specifications of the data formats, sample code, and evaluation tools.

关键词： Cameras Simultaneous localization and mapping Calibration Trajectory Visualization

来源：评论

学校读者我要写书评

暂无评论

Towards Practical Visual Servoing in robotics

Towards Practical Visual Servoing in Robotics

引用

Canadian Conference on computer and Robot vision, CRV

作者： Romeo Tatsambon Fomena Camilo Perez Quintero Mona Gridseth Martin Jagersand Computer Vision and Robotics Research Group Department of Computing Science University of Alberta Edmonton AB Canada

ISBN: (纸本)9781467364096

Visual servoing was introduced in robotics nearly 4 decades ago. However until now, there are still only a handful of known examples of application of this technique in addressing real word robotics problems such as disaster response, assistance for elderly or handicapped people, etc. As the world is moving towards the use of robotics to improve quality of life, it is time to assess the challenges involved in applying visual servoing to solve real world problems. This paper presents an overview of these challenges, by asking the question what are the missing components for practical visual servoing? and by providing practical possible solutions for these components. Illustration of these challenges and our current practical solutions are given using our 7-DoFs Barrett WAM Arm.

关键词： Visual servoing Visualization Cameras Target tracking Robot kinematics

来源：评论

学校读者我要写书评

暂无评论

Dependence Tree Structure Estimation via Copula

引用

International Journal of Automation and computing 2012年第2期9卷 113-121页

作者： Jian Ma Zeng-Qi Sun Sheng Chen Hong-Hai Liu Department of Computer Science Tsinghua University Beijing 100084 PRC Electronics and Computer Science Faculty of Physical and Applied Sciences University of Southampton Southampton SO17 1B J UK Faculty of Engineering King Abdulaziz University Jeddah 21589 Saudi Arabia Intelligent Systems and Robotics Research Group School of Creative Technologies University of Portsmouth Portsmouth PO1 2D J UK

We propose an approach for dependence tree structure learning via copula. A nonparametric algorithm for copula estimation is presented. Then a Chow-Liu like method based on dependence measure via copula is proposed to estimate maximum spanning bivariate copula associated with bivariate dependence relations. The main advantage of the approach is that learning with empirical copula focuses on dependence relations among random variables, without the need to know the properties of individual variables as well as without the requirement to specify parametric family of entire underlying distribution for individual variables. Experiments on two real-application data sets show the effectiveness of the proposed method.

关键词： Copula empirical copula dependence tree structure learning probability distribution.

来源：评论

学校读者我要写书评

暂无评论

Measuring bilateral symmetry in digital images

Measuring bilateral symmetry in digital images

引用

IEEE Region 10 International Conference TENCON

作者： D. O'Mara R. Owens Robotics & Vision Research Group Department of Computer Science University of Western Australia Nedlands WA Australia

An important example of bilateral symmetry in nature is the approximate bilateral symmetry exhibited by humans. Detecting and measuring bilateral symmetry in medical images should provide benefits in a clinical environment. This paper presents a method for detecting the dominant plane of bilateral symmetry in an image of arbitrary dimension and subsequently measuring the degree of bilateral symmetry in the image. By adapting the work of others, we provide a unique solution to the problem by using a simple representation of the data and a more sensitive measure of symmetry.

关键词： Digital images Image edge detection Humans Biomedical imaging Magnetic field measurement Data compression Reflection Medical robotics Robot vision systems Anthropometry

来源：评论

学校读者我要写书评

暂无评论

Corrigendum to “PSFHS challenge report: pubic symphysis and fetal head segmentation from intrapartum ultrasound images” [Medical Image Analysis 99 (2025),103353]

引用

Medical Image Analysis 2025年 103651页

作者： Jieyun Bai Zihao Zhou Zhanhong Ou Gregor Koehler Raphael Stock Klaus Maier-Hein Marawan Elbatel Robert Martí Xiaomeng Li Yaoyang Qiu Panjie Gou Gongping Chen Lei Zhao Jianxun Zhang Yu Dai Fangyijie Wang Guénolé Silvestre Kathleen Curran Hongkun Sun Jing Xu Karim Lekadir Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization Jinan University Guangzhou China Auckland Bioengineering Institute The University of Auckland Auckland New Zealand Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Department of Computer Science and Engineering The Chinese University of Hong Kong China Computer Vision and Robotics Group University of Girona Girona Spain Canon Medical Systems (China) Co. LTD Beijing China College of Artificial Intelligence Nankai University Tianjin China College of Computer Science and Electronic Engineering Hunan University Changsha China School of Medicine University College Dublin Dublin Ireland School of Computer Science University College Dublin Dublin Ireland School of Statistics & Mathematics Zhejiang Gongshang University Hangzhou China Departament de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Institució Catalana de Recerca i Estudis Avançats (ICREA) Barcelona Spain

来源：评论

学校读者我要写书评

暂无评论

The second international conference on Human-Robot Interaction

The second international conference on Human-Robot Interacti...

引用

作者： Schultz, Alan C. Breazeal, Cynthia Fong, Terry Kiesler, Sara Washington DC United States Department of Media Arts and Scienes MIT Media Lab. Intelligent Robotics Group NASA Ames Research Center Department of Computer Science and Human Computer Interaction Carnegie Mellon University Pittsburgh PA United States

The second international conference on Human-Robot Interaction (HRI-2007) was held in Arlington, Virginia, March 9-11, 2007. The theme of the conference was "Robot as Team Member" and included posters and paper presentations on teamwork, social robotics, adaptation, observation and metrics, attention, user experience, and field testing. One hundred seventy-five researchers and practitioners attended the conference, and many more contributed to the conference as authors or reviewers. HRI-2008 will be held in Amsterdam, The Netherlands from March 12-15, 2008. Copyright © 2007, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： robotics

来源：评论

学校读者我要写书评

暂无评论

Detailed dense inference with convolutional neural networks via discrete wavelet transform

arXiv

引用

arXiv 2018年

作者： Ma, Lingni Stückler, Jörg Wu, Tao Cremers, Daniel Computer Vision and Artificial Intelligence Group Computer Science Department Technical University of Munich Max Planck Institute for Intelligent Systems

Dense pixelwise prediction such as semantic segmentation is an up-to-date challenge for deep convolutional neural networks (CNNs). Many state-of-the-art approaches either tackle the loss of high-resolution information due to pooling in the encoder stage, or use dilated convolutions or high-resolution lanes to maintain detailed feature maps and predictions. Motivated by the structural analogy between multi-resolution wavelet analysis and the pooling/unpooling layers of CNNs, we introduce discrete wavelet transform (DWT) into the CNN encoder-decoder architecture and propose WCNN. The high-frequency wavelet coefficients are computed at encoder, which are later used at the decoder to unpooled jointly with coarse-resolution feature maps through the inverse DWT. The DWT/iDWT is further used to develop two wavelet pyramids to capture the global context, where the multi-resolution DWT is applied to successively reduce the spatial resolution and increase the receptive field. Experiment with the Cityscape dataset, the proposed WCNNs are computationally efficient and yield improvements the accuracy for high-resolution dense pixelwise prediction. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

CARL: Camera-Agnostic Representation Learning for Spectral Image Analysis

arXiv

引用

arXiv 2025年

作者： Baumann, Alexander Ayala, Leonardo Seidlitz, Silvia Sellner, Jan Studier-Fischer, Alexander Özdemir, Berkin Maier-Hein, Lena Ilic, Slobodan Siemens AG Munich Germany Heidelberg Germany Medical Faculty Faculty of Mathematics and Computer Science Heidelberg University Germany NCT Heidelberg Germany HIDSS4Health Heidelberg Germany Department of Urology and Urosurgery University Medical Center Mannheim Germany Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Germany Division of Intelligent Systems and Robotics in Urology DKFZ Heidelberg Germany DKFZ Hector Cancer Institute University Medical Center Mannheim Germany

Spectral imaging offers promising applications across diverse domains, including medicine and urban scene understanding, and is already established as a critical modality in remote sensing. However, variability in channel dimensionality and captured wavelengths among spectral cameras impede the development of AI-driven methodologies, leading to camera-specific models with limited generalizability and inadequate cross-camera applicability. To address this bottleneck, we introduce CARL, a model for Camera-Agnostic Representation Learning across RGB, multispectral, and hyperspectral imaging modalities. To enable the conversion of a spectral image with any channel dimensionality to a camera-agnostic embedding, we introduce wavelength positional encoding and a self-attention-cross-attention mechanism to compress spectral information into learned query representations. Spectral-spatial pre-training is achieved with a novel spectral self-supervised JEPA-inspired strategy tailored to CARL. Large-scale experiments across the domains of medical imaging, autonomous driving, and satellite imaging demonstrate our model’s unique robustness to spectral heterogeneity, outperforming on datasets with simulated and real-world cross-camera spectral variations. The scalability and versatility of the proposed approach position our model as a backbone for future spectral foundation models. © 2025, CC BY.

关键词： Image coding

来源：评论

学校读者我要写书评

暂无评论

Hardware-in-the-loop simulation of a UAV autonomous landing algorithm implemented in SoC FPGA

arXiv

引用

arXiv 2022年

作者： Szolc, Hubert Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

This paper presents a system for hardware-in-the-loop (HiL) simulation of unmanned aerial vehicle (UAV) control algorithms implemented on a heterogeneous SoC FPGA computing platforms. The AirSim simulator running on a PC and an Arty Z7 development board with a Zynq SoC chip from AMD Xilinx were used. Communication was carried out via a serial USB link. An application for autonomous landing on a specially marked landing strip was selected as a case study. A landing site detection algorithm was implemented on the Zynq SoC platform. This allowed processing a 1280 × 720 @ 60 fps video stream in real time. Performed tests showed that the system works correctly and there are no delays that could negatively affect the stability of the control. The proposed concept is characterised by relative simplicity and low implementation cost. At the same time, it can be applied to test various types of high-level perception and control algorithms for UAV implemented on embedded platforms. We provide the code developed on GitHub, which includes both Python scripts running on the PC and C code running on Arty Z7. © 2022, CC BY.

关键词： System-on-chip

来源：评论

学校读者我要写书评

暂无评论

Energy Efficient Hardware Acceleration of Neural Networks with Power-of-Two Quantisation

TechRxiv

引用

TechRxiv 2022年

作者： Przewlocka-Rus, Dominika Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

Deep neural networks virtually dominate the domain of most modern vision systems, providing high performance at a cost of increased computational complexity. Since for those systems it is often required to operate both in real-time and with minimal energy consumption (e.g., for wearable devices or autonomous vehicles, edge Internet of Things (IoT), sensor networks), various network optimisation techniques are used, e.g., quantisation, pruning, or dedicated lightweight architectures. Due to the logarithmic distribution of weights in neural network layers, a method providing high performance with significant reduction in computational precision (for 4-bit weights and less) is the Power-of-Two (PoT) quantisation (and therefore also with a logarithmic distribution). This method introduces additional possibilities of replacing the typical for neural networks Multiply and ACcumulate (MAC – performing, e.g., convolution operations) units, with more energy-efficient Bitshift and ACcumulate (BAC). In this paper, we show that a hardware neural network accelerator with PoT weights implemented on the Zynq UltraScale + MPSoC ZCU104 SoC FPGA can be at least 1.4x more energy efficient than the uniform quantisation version. To further reduce the actual power requirement by omitting part of the computation for zero weights, we also propose a new pruning method adapted to logarithmic quantisation. © 2022, CC BY.

关键词： System-on-chip

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：