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1st International Workshop on Pen-Based Learning Technologies, PLT 2007

作者： Iannizzotto, Giancarlo Rosa, Francesco La VisiLab Computer Vision and Human-Computer Interaction Lab. Faculty of Engineering University of Messina C.da Di Dio 98166 Messina Italy

ISBN: (纸本)0769529429

In this paper we describe a pen-based user interface for easy and natural user interaction with a wall projection display. VisualPen is a vision-based system for real-time detection and tracking of a pen that completely replaces mouse and keyboard. The low computational complexity of its algorithms renders it easy to implement with low-cost, lowpower embedded hardware, thus allowing portability and integrability. The architecture of the system is described, and experimental results are presented and commented.

关键词： User interfaces

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A simple, usable and robust solution for pen-based interaction on projection displays

A simple, usable and robust solution for pen-based interacti...

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International Workshop on Pen-Based Learning Technologies, PLT

作者： Giancarlo Iannizzotto Francesco La Rosa VisiLab Computer Vision and Human-Computer Interaction Laboratory Engineering University of Messina Messina Italy

In this paper we describe a pen-based user interface for easy and natural user interaction with a wall projection display. VisualPen is a vision-based system for real-time detection and tracking of a pen that completely replaces mouse and keyboard. The low computational complexity of its algorithms renders it easy to implement with low-cost, low-power embedded hardware, thus allowing portability and integrability. The architecture of the system is described, and experimental results are presented and commented.

关键词： Robustness Displays User interfaces Real time systems Mice Keyboards Computational complexity Rendering (computer graphics) Hardware computer architecture

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Semantic Visual Simultaneous Localization and Mapping: A Survey

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IEEE Transactions on Intelligent Transportation Systems 2025年第6期26卷 7426-7449页

作者： Chen, Kaiqi Xiao, Junhao Liu, Jialing Tong, Qiyi Zhang, Heng Liu, Ruyu Zhang, Jianhua Ajoudani, Arash Chen, Shengyong Zhejiang University of Technology Institute of Computer Vision College of Computer Science and Technology Hangzhou 310023 China Istituto Italiano di Tecnologia Human-Robot Interfaces and Interaction Laboratory Genoa 16163 Italy National University of Defense Technology College of Intelligence Science and Technology Changsha 410073 China Universitã di Genova Ph.D. Program of National Interest in Robotics and Intelligent Machines (DRIM) Genoa 16126 Italy Hangzhou Normal University School of Information Science and Technology Hangzhou 311121 China Technical University of Denmark Department of Technology Management and Economics Kongens Lyngby 2800 Denmark Tianjin University of Technology Institute of Computer Vision School of Computer Science and Engineering Tianjin 300384 China

Visual Simultaneous Localization and Mapping (vSLAM) is a cornerstone technology in computer vision and robotics, underpinning applications such as autonomous vehicles and robot navigation. While traditional vSLAM systems have shown significant progress in indoor or outdoor environments, their performance often degrades in complex scenes, limiting their adaptability and robustness. Semantic vSLAM, which integrates high-level semantic information into vSLAM systems, has emerged as a promising solution to address these limitations by enabling a richer understanding of the environment. In this paper, we provide a comprehensive review of semantic vSLAM, offering a critical analysis of its evolution, methods, and challenges. We begin by revisiting the development of traditional vSLAM, emphasizing its limitations and the motivation for incorporating semantic information. Subsequently, we delve into the core modules of semantic vSLAM, including semantic extraction, object association, semantic loop closing, back-end optimization, and semantic mapping. Then, we present a performance comparison of semantic vSLAM systems under two different datasets, indoor and outdoor, respectively. Furthermore, we also provide a comparative analysis of widely used SLAM datasets to provide guidance for performance testing and validation. To further enrich the discussion, we identify unresolved challenges in semantic vSLAM, such as long-term semantic perception and association, open and unstructured environments. We propose future research directions, including balancing computational resources and quantifying system risk, large model-based navigation and mapping, and embodied AI SLAM. By providing key insights and forward-looking perspectives, this work aims to stimulate future research and improve the capabilities of semantic vSLAM in real-world applications. © 2000-2011 IEEE.

关键词： localization mapping semantic information Semantic visual SLAM SLAM datasets

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Improving marker-based tracking for augmented reality in underwater environments

Improving marker-based tracking for augmented reality in und...

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2018 Eurographics Workshop on Graphics and Cultural Heritage, GCH 2018

作者： Cejka, Jan Marek, U. Agrafiotis, Panagiotis Skarlatos, Dimitrios Bruno, Fabio Liarokapis, Fotis Human Computer Interaction Laboratory Faculty of Informatics Masaryk University Czech Republic Photogrammetric Vision Laboratory Department of Civil Engineering and Geomatics Cyprus University of Technology Cyprus Cyprus Research S.r.l. - University of Calabria Italy

ISBN: (纸本)9783038680574

Underwater sites are a challenging environment for augmented reality. Images taken under water are degraded in several ways, most importantly they are affected by unbalanced colors due to uneven absorption of light in each color channel, blurring and desaturation caused by turbidity, or noise due to the presence of larger organisms, plants, or bubbles. In this paper, we introduce a new method based on white balancing that enhances underwater images to improve the results of detection of markers. We compare this method with several image enhancement methods, and evaluate their performance when applied to the problem of detecting markers under water. Our results show that our method improves the detection in underwater environments while keeping the computation time low. © 2018 GCH 2018 - Eurographics Workshop on Graphics and Cultural Heritage. All rights reserved.

关键词： Augmented reality

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Independent component analysis in a facial local residue space

Independent component analysis in a facial local residue spa...

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Tae-Kyun Kim Hyunwoo Kim Wonjun Hwang Seok-Cheol Kee J. Kittler Centre for Vision Speech and Signal Processing University of Surrey UK Human Computer Interaction Laboratory Samsung Advanced Institute of Technology South Korea

In this paper, we propose an ICA (Independent Component Analysis) based face recognition algorithm, which is robust to illumination and pose variation. Generally, it is well known that the first few eigenfaces represent illumination variation rather than identity. Most PCA (Principal Component Analysis)-based methods have overcome illumination variation by discarding the projection to a few leading eigenfaces. The space spanned after removing a few leading eigenfaces is called the "residual face space". We found that ICA in the residual face space provides more efficient encoding in terms of redundancy reduction and robustness to pose variation as well as illumination variation, owing to its ability to represent non-Gaussian statistics. Moreover, a face image is separated into several facial components, local spaces, and each local space is represented by the ICA bases (independent components) of its corresponding residual space. The statistical models of face images in local spaces are relatively simple and facilitate classification by a linear encoding. Various experimental results show that the accuracy of face recognition is significantly improved by the proposed method under large illumination and pose variations.

关键词： Independent component analysis Principal component analysis Face recognition Lighting Statistics Image databases Face detection Space technology Speech analysis Signal processing algorithms

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Learning Robust Representations with Information Bottleneck and Memory Network for RGB-D-based Gesture Recognition

Learning Robust Representations with Information Bottleneck ...

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International Conference on computer vision (ICCV)

作者： Yunan Li Huizhou Chen Guanwen Feng Qiguang Miao School of Computer Science and Technology Xidian University China Xi’an Key Laboratory of Big Data and Intelligent Vision China Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province China

Although previous RGB-D-based gesture recognition methods have shown promising performance, researchers often overlook the interference of task-irrelevant cues like illumination and background. These unnecessary factors are learned together with the predictive ones by the network and hinder accurate recognition. In this paper, we propose a convenient and analytical framework to learn a robust feature representation that is impervious to gesture-irrelevant factors. Based on the Information Bottleneck theory, two rules of Sufficiency and Compactness are derived to develop a new information-theoretic loss function, which cultivates a more sufficient and compact representation from the feature encoding and mitigates the impact of gesture-irrelevant information. To highlight the predictive information, we further integrate a memory network. Using our proposed content-based and contextual memory addressing scheme, we weaken the nuisances while preserving the task-relevant information, providing guidance for refining the feature representation. Experiments conducted on three public datasets demonstrate that our approach leads to a better feature representation and achieves better performance than state-of-the-art methods. The code of our method is available at: https://***/Carpumpkin/InBoMem.

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A collaborative approach for human-centered driver assistance systems

A collaborative approach for human-centered driver assistanc...

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International Conference on Intelligent Transportation

作者： J.C. McCall O. Achler M.M. Trivedi J.-B. Haue P. Fastrez D. Forster J.D. Hollan E. Boer Computer Vision and Robotics Research Laboratory Distributed Cognition and Human Computer Interaction Laboratory University of California San Diego USA ERB Consulting and Cal-IT University of California San Diego La Jolla CA USA

This paper describes an interdisciplinary research collaboration to design a human-centered driver assistance system. Driving behavior is captured using a novel intelligent vehicle test bed. The synchronized capture o... 详细信息

关键词： Collaboration Vehicle driving Cognition Streaming media Laboratories Intelligent vehicles Intelligent systems System testing Data analysis Video compression

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Development of a child-oriented social robot for safe and interactive physical interaction

Development of a child-oriented social robot for safe and in...

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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Xiaoning Ma Francis Quek Social Robotics Laboratory Interactive and Digital Institute National University of Singapore Singapore Vision Interfaces and Systems Laboratory Center of Human Computer Interaction Virginia Polytechnic Institute and State University Blacksburg VA USA

As an important approach to ensure safety and naturalness, compliant motion is already implemented in large-size robots, but it is still an undeveloped area in child-oriented robots as it calls for a lightweight and compact solution compared with large-size robots. In this paper, we proposed the design of a social robot which aims at conducting safe and playful human-Robot interaction (HRI), especially with children. We built a teddy bear robot prototype based on hybrid passive-active compliant system which consists of flexible joints as passive part and compliant motion controller as active part. The compliant controller detects external perturbation through motor state variables, therefore force and torque sensors could be omitted to keep overall system compact. Experiments conducted in typical HRI scenarios showed that the hybrid passive-active compliant system enabled our robot to conduct safer and more interactive physical interaction compared with robot under traditional control method.

关键词： Robot sensing systems Torque Joints Equations Mathematical model humans

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Flexible disaster response of tomorrow final presentation and evaluation of the CENTAURO system

arXiv

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arXiv 2019年

作者： Klamt, Tobias Rodriguez, Diego Baccelliere, Lorenzo Chen, Xi Chiaradia, Domenico Cichon, Torben Gabardi, Maßimiliano Guria, Paolo Holmquist, Karl Kamedula, Malgorzata Karaoguz, Hakan Kashiri, Navvab Laurenzi, Arturo Lenz, Christian Leonardis, Daniele Hoffman, Enrico Mingo Muratore, Luca Pavlichenko, Dmytro Porcini, Francesco Ren, Zeyu Schilling, Fabian Schwarz, Max Solazzi, Maßimiliano Felsberg, Michael Frisoli, Antonio Gustmann, Michael Jensfelt, Patric Nordberg, Klas Roßmann, Jürgen Süß, Uwe Tsagarakis, Nikos G. Behnke, Sven Autonomous Intelligent Systems University of Bonn Germany Humanoids and Human-Centred Mechatronics Istituto Italiano di Tecnologia Genoa Italy Department of Robotics Perception and Learning KTH Royal Institute of Technology Stockholm Sweden PERCRO Laboratory TeCIP Institute Sant'Anna School of Advanced Studies Pisa Italy Institute for Man-Machine Interaction RWTH Aachen University Germany Computer Vision Laboratory Linköping University Sweden Lausanne Switzerland Kerntechnische Hilfsdienst GmbH Karlsruhe Germany School of Electrical and Electronic Engineering University of Manchester United Kingdom

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New Methods on Image Analysis, Two Applications: An Augmented Reality Application for Heartbeat Sound Analysis And A MRI Brain Injury Image Analysis

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Journal of Physics: Conference Series 2019年第1期1229卷

作者： L J Lechuga T Yamamoto O López G Lechuga Japanese International Cooperation Agency (JICA) trainee program at the Kanazawa Institute of Technology 7-1 Ohgigaoka Nonoichi Ishikawa / 921 - 8501 Japan Human interaction laboratory Kanazawa Institute of Technology 7-1 Ohgigaoka Nonoichi Ishikawa / 921 - 8501 Japan Industrial Engineering Department ITESM calle del Puente 222 Ejidos de Huipulco 13480 CDMX Mexico Computer Vision Detection ENGIE 1 place Samuel de Champlain 92400 Courbevoie- France

Traditional statistical methods have become insufficient when applied to image analysis. The increasing size of data volume and its complexity demands new statistical approaches and algorithms. Current methods imply losing intrinsic data structures, for example when data comes from multiway arrays. In this work we concentrate in two applications i) A pre-diagnostic smartphone application for detection of cardiovascular abnormalities through the analysis of heartbeat sounds and the use of augmented reality for displaying valuable information to the end user in an immersive experience. Using the latest augmented reality smartphone applications, a digital stethoscope, heartbeat audios and classification using neural networks, we measure a user's heartbeat and output in real time, a pre-diagnostic of their current cardiovascular health. ii) A study concerning comatose patients, based on a Diffusion Tensor Image Magnetic Resonance Imaging (MRI) dataset that predicts long-term outcome for patients having suffered a brain traumatic injury. MRI images were obtained from 104 comatose patients, 65 with positive outcome and 39 with negative outcome, 39 controls were used. The fact that each volumetric image led into a 143x255726x4 tensor input, is used to briefly explain how new multiway methods could be useful in image analysis methods.

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