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Monocular real-time 3D articulated hand pose estimation

Monocular real-time 3D articulated hand pose estimation

引用

9th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS09

作者： Romero, Javier Kjellström, Hedvig Kragic, Danica Computational Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication SE-IOO 44 Stockholm Sweden

ISBN: (纸本)9781424445882

Markerless, vision based estimation of human hand pose over time is a prerequisite for a number of robotics applications, such as Learning by Demonstration (LbD), health monitoring, teleoperation, human-robot interaction. It has special interest in humanoid platforms, where the number of degrees of freedom makes conventional programming challenging. Our primary application is LbD in natural environments where the humanoid robot learns how to grasp and manipulate object by observing a human performing a task. This paper presents a method for continuous vision based estimation of human hand pose. The method is non-parametric, performing a nearest neighbor search in a large database (100000 entries) of hand pose examples. The main contribution is a real time system, robust to partial occlusions and segmentation errors, that provides full hand pose recognition from markerless data. An additional contribution is the modeling of constraints based on temporal consistency in hand pose, without explicitly tracking the hand in the high dimensional pose space. The pose representation is rich enough to enable a descriptive humanto-robot mapping. Experiment show the pose estimation to be more robust and accurate than a non-parametric method without temporal constraints. ©2009 IEEE.

关键词： Nearest neighbor search

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Tracking of fingertips and centers of palm using KINECT

Tracking of fingertips and centers of palm using KINECT

引用

2nd International Conference on Computational Intelligence, Modelling and Simulation 2011, CIMSim 2011

作者： Raheja, Jagdish L. Chaudhary, Ankit Singal, Kunal Machine Vision Lab. Digital Systems Group CEERI/CSIR Pilani Rajasthan India Computer Vision Research Group BITS Pilani Rajasthan India Punjab Engineering College Chandigarh India

ISBN: (纸本)9780769545622

Hand Gesture is a popular way to interact or control machines and it has been implemented in many applications. The geometry of hand is such that it is hard to construct in virtual environment and control the joints but the functionality and DOF encourage researchers to make a hand like instrument. This paper presents a novel method for fingertips detection and centres of palms detection distinctly for both hands using MS KINECT in 3D from the input image. KINECT facilitates us by providing the depth information of foreground objects. The hands were segmented using the depth vector and centres of palms were detected using distance transformation on inverse image. This result would be used to feed the inputs to the robotic hands to emulate human hands operation. © 2011 IEEE.

关键词： Image segmentation

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Interactive Editing of Live Visuals

Interactive Editing of Live Visuals

引用

1st International Conferences on computer vision Theory and Applications, VISAPP 2006, and International Conference on computer Graphics Theory and Applications, GRAPP 2006

作者： Müller, Pascal Müller Arisona, Stefan Schubiger-Banz, Simon Specht, Matthias Computer Vision Lab ETH Zürich Switzerland Computer Systems Institute ETH Zürich Switzerland Swisscom Innovations Switzerland Anthropological Institute University of Zürich Switzerland

ISBN: (纸本)9783540752721

This paper describes novel concepts for the interactive composition of artistic real-time graphics, so-called live visuals. By establishing two fundamental techniques dealing with the structured media integration and the intrinsic design process, we significantly increase the efficiency of interactive editing in live visuals applications. First, we present a media manager that supports the user in both retrieval and utilization of automatically annotated digital media. The computer-assisted application of individual media items permits the interactive control of non-linear editing (NLE) of video in real-time. Second, we optimize the design process by introducing the design tree, which collects and organizes the artist's work in an intuitive way. Design tree operations provide interactive high-level editing methods which allow for exploration, combination, reuse, and evolution of designs before and particularly during the performance. We examined the effectiveness of our techniques on numerous long-lasting live performances from which representative examples are demonstrated. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Digital storage

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Interest point based tracking

Interest point based tracking

引用

2010 20th International Conference on Pattern Recognition, ICPR 2010

作者： Kloihofer, Werner Kampel, Martin Research and Development Image Processing Center Communication Systems GmbH Vienna Austria Computer Vision Lab. Vienna University of Technology Vienna Austria

ISBN: (纸本)9780769541099

This paper deals with a novel method for object tracking. In the first step interest points are detected and feature descriptors around them are calculated. Sets of known points are created, allowing tracking based on point matching. The set representation is updated online at every tracking step. Our method uses one-shot learning with the first frame, so no offline and no supervised learning is required. Following an object recognition based approach there is no need for a background model or motion model, allowing tracking of abrupt motion and with non-stationary cameras. We compare our method to MeanShift and Tracking via Online Boosting, showing the benefits of our approach. © 2010 IEEE.

关键词： Object detection

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Quantum Annealing for the Mechanics of Robot Inspectors on Electrical Transmission Lines' Conductors

Quantum Annealing for the Mechanics of Robot Inspectors on E...

引用

2024 International Conference on Control, Robotics and Informatics, ICCRI 2024

作者： Salloum, Hadi Bahrami, Mohammad Reza Matevosian, Artem Gamershmidt, Sofia Jnadi, Ali Mazzara, Manuel Innopolis University Faculty of Computer Science and Engineering Innopolis Russia Innopolis University Cyber-physical systems lab Innopolis Russia Institute of Robotics and Computer Vision Innopolis University Innopolis Russia

ISBN: (纸本)9798350380309

This paper explores the integration of quantum computing, specifically quantum annealing, into robotics for inspecting electrical transmission lines. By using quantum annealing's computational power, we address the dynamics of robot inspectors on transmission line conductors, enhancing the computational efficiency of managing the movements of robot inspectors on transmission line conductors. The use of these robots is crucial for performing efficient and safe inspections. We discuss the mathematical foundations of quantum annealing, transforming differential equations governing robot dynamics into Ising model Hamiltonians suitable for quantum annealing devices. Through experiments using D-Wave's 'Advantage' quantum annealer, we demonstrate the viability of quantum annealing in solving complex robotics problems, paving the way for advanced applications in the field. © 2024 IEEE.

关键词： Ising model

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SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation 35

SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

引用

35th Conference on Neural Information Processing systems - Track on Datasets and Benchmarks, NeurIPS Datasets and Benchmarks 2021

作者： Chan, Robin Lis, Krzysztof Uhlemeyer, Svenja Blum, Hermann Honari, Sina Siegwart, Roland Fua, Pascal Salzmann, Mathieu Rottmann, Matthias Stochastics Group IZMD University of Wuppertal Wuppertal Germany Computer Vision Laboratory EPFL Lausanne Switzerland Autonomous Systems Lab ETH Zürich Switzerland

State-of-the-art semantic or instance segmentation deep neural networks (DNNs) are usually trained on a closed set of semantic classes. As such, they are ill-equipped to handle previously-unseen objects. However, detecting and localizing such objects is crucial for safety-critical applications such as perception for automated driving, especially if they appear on the road ahead. While some methods have tackled the tasks of anomalous or out-of-distribution object segmentation, progress remains slow, in large part due to the lack of solid benchmarks;existing datasets either consist of synthetic data, or suffer from label inconsistencies. In this paper, we bridge this gap by introducing the "SegmentMeIfYouCan" benchmark. Our benchmark addresses two tasks: Anomalous object segmentation, which considers any previously-unseen object category;and road obstacle segmentation, which focuses on any object on the road, may it be known or unknown. We provide two corresponding datasets together with a test suite performing an in-depth method analysis, considering both established pixel-wise performance metrics and recent component-wise ones, which are insensitive to object sizes. We empirically evaluate multiple state-of-the-art baseline methods, including several models specifically designed for anomaly / obstacle segmentation, on our datasets and on public ones, using our test suite. The anomaly and obstacle segmentation results show that our datasets contribute to the diversity and difficulty of both data landscapes. © 2021 Neural information processing systems foundation. All rights reserved.

关键词： Semantic Segmentation

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Object recognition via local patch labelling

Object recognition via local patch labelling

引用

First International Workshop on Deterministic and Statistical Methods in Machine Learning

作者： Bishop, Christopher M. Ulusoy, Ilkay Microsoft Research 7 J J Thompson Avenue Cambridge United Kingdom METU Computer Vision and Intelligent Systems Research Lab. 06531 Ankara Turkey

ISBN: (纸本)3540290737

In recent years the problem of object recognition has received considerable attention from both the machine learning and computer vision communities. The key challenge of this problem is to be able to recognize any member of a category of objects in spite of wide variations in visual appearance due to variations in the form and colour of the object, occlusions, geometrical transformations (such as scaling and rotation), changes in illumination, and potentially non-rigid deformations of the object itself. In this paper we focus on the detection of objects within images by combining information from a large number of small regions, or 'patches', of the image. Since detailed hand-segmentation and labelling of images is very labour intensive, we make use of 'weakly labelled' data in which the training images are labelled only according to the presence or absence of each category of object. A major challenge presented by this problem is that the foreground object is accompanied by widely varying background clutter, and the system must learn to distinguish the foreground from the background without the aid of labelled data. In this paper we first show that patches which are highly relevant for the object discrimination problem can be selected automatically from a large dictionary of candidate patches during learning, and that this leads to improved classification compared to direct use of the full dictionary. We then explore alternative techniques which are able to provide labels for the individual patches, as well as for the image as a whole, so that each patch is identified as belonging to one of the object categories or to the background class. This provides a rough indication of the location of the object or objects within the image. Again these individual patch labels must be learned on the basis only of overall image class labels. We develop two such approaches, one discriminative and one generative, and compare their performance both in terms of patch labelling and

关键词： Object recognition

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Task-based grasp adaptation on a humanoid robot

Task-based grasp adaptation on a humanoid robot

引用

10th IFAC Symposium on Robot Control, SYROCO 2012

作者： Bohg, Jeannette Welke, Kai León, Beatriz Do, Martin Song, Dan Wohlkinger, Walter Madry, Marianna Aldóma, Aitor Przybylski, Markus Asfour, Tamim Martí, Higinio Kragic, Danica Morales, Antonio Vincze, Markus Humanoids and Intelligence Systems Lab. Institute for Anthropomatics KIT Germany Autonomous Motion Lab. MPI for Intelligent Systems Germany Robotic Intelligence Laboratory Department of Computer Science and Engineering UJI Spain Computer Vision and Active Perception Lab. KTH Sweden Automation and Control Institute TUW Austria

ISBN: (纸本)9783902823113

In this paper, we present an approach towards autonomous grasping of objects according to their category and a given task. Recent advances in the field of object segmentation and categorization as well as task-based grasp inference have been leveraged by integrating them into one pipeline. This allows us to transfer task-specific grasp experience between objects of the same category. The effectiveness of the approach is demonstrated on the humanoid robot ARMAR-IIIa. © 2012 IFAC.

关键词： Anthropomorphic robots

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Grasp recognition and mapping on humanoid robots

Grasp recognition and mapping on humanoid robots

引用

9th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS09

作者： Do, Martin Romero, Javier Kjellström, Hedvig Azad, Pedram Asfour, Tamim Kragic, Danica Dillmann, Rüdiger KTH - Royal Institute of Technology Stockholm Sweden Computer Vision and Active Perception Lab. Centre for Autonomous Systems Sweden Karlsruhe Germany Institute for Anthropomatics Germany

ISBN: (纸本)9781424445882

In this paper, we present a system for vision-based grasp recognition, mapping and execution on a humanoid robot to provide an intuitive and natural communication channel between humans and humanoids. This channel enables a human user to teach a robot how to grasp an object. The system comprises three components: human upper body motion capture system which provides the approaching direction towards an object, hand pose estimation and grasp recognition system, which provides the grasp type performed by the human as well as a grasp mapping and execution system for grasp reproduction on a humanoid robot with five-fingered hands. All three components are real-time and markerless. Once an object is reached, the hand posture is estimated, including hand orientation and grasp type. For the execution on a robot, hand posture and approach movement are mapped and optimized according to the kinematic limitations of the robot. Experimental results are performed on the humanoid robot ARMAR-IIIb. ©2009 IEEE.

关键词： Anthropomorphic robots

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Cooperative object path following control by means of mobile manipulators: A switched systems approach

Cooperative object path following control by means of mobile...

引用

10th IFAC Symposium on Robot Control, SYROCO 2012

作者： Markdahl, Johan Karayiannidis, Yiannis Hu, Xiaoming Division of Optimization and Systems Theory KTH Royal Institute of Technology Stockholm Sweden Computer Vision and Active Perception Lab. KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9783902823113

This paper proposes a switched control algorithm for distributed cooperative manipulation of rigid bodies in a planar setting. More specifically, we consider the problem of making a grasped object follow a desired position and orientation path. The system contains N robots, possibly of heterogeneous designs, each of which consists of a manipulator arm and a nonholonomic mobile platform. Control is based on local information, is carried out on a kinematic level and partly utilizes inverse kinematics. We use Lyapunov-like arguments to prove that the algorithm is almost globally stable and also show that its parameters can be chosen so that any input saturation level is met. The time between certain switches is proved to be bounded below, and the system is shown to be free of any Zeno behavior. © 2012 IFAC.

关键词： Inverse kinematics

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