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IEEE Biomedical Circuits and Systems (BIOCAS)

作者： Garrick Orchard Chiara Bartolozzi Giacomo Indiveri Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA Robotics Brain and Cognitive Sciences Department Italian Institute of Technology Italy Institute of Neuroinformatics University of Zurich Zurich Switzerland

Recently there has been an increasing interest in application of bio-mimetic controllers and neuromorphic vision sensors to planetary landing tasks. Within this context, we present combined low-level (SPICE) and high-level (behavioral) simulations of a novel neuromorphic VLSI vision sensor in a realistic planetary landing scenario. We use results from low level simulations to build an abstract description of the chip which can be used in higher level simulations which include closed-loop control of the craft.

关键词： Neuromorphics Biosensors Circuit simulation SPICE Biology computing Distributed computing Physics computing Surface topography Computer vision Signal processing

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A monocular pointing pose estimator for gestural instruction of a mobile robot

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International Journal of Advanced Robotic Systems 2007年第1 SPEC. ISS.期4卷 139-150页

作者： Richarz, Jan Scheidig, Andrea Martin, Christian Müller, Steffen Gross, Horst-Michael Intelligent Systems Group Robotics Research Institute University of Dortmund Germany Department of Neuroinformatics and Cognitive Robotics Ilmenau Technical University Germany

We present an important aspect of our human-robot communication interface which is being developed in the context of our long-term research framework PERSES dealing with highly interactive mobile companion robots. Based on a multi-modal people detection and tracking system, we present a hierarchical neural architecture that estimates a target point at the floor indicated by a pointing pose, thus enabling a user to navigate a mobile robot to a specific target position in his local surroundings by means of pointing. In this context, we were especially interested in determining whether it is possible to accomplish such a target point estimator using only monocular images of low-cost cameras. The estimator has been implemented and experimentally investigated on our mobile robotic assistant HOROS. Although only monocular image data of relatively poor quality were utilized, the estimator accomplishes a good estimation performance, achieving an accuracy better than that of a human viewer on the same data. The achieved recognition results demonstrate that it is in fact possible to realize a user-independent pointing direction estimation using monocular images only, but further efforts are necessary to improve the robustness of this approach for everyday application.

关键词： Gesture recognition

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Tracking of Human Body Parts using the Multiocular Contracting Curve Density Algorithm

Tracking of Human Body Parts using the Multiocular Contracti...

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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： Markus Hahn Lars Kruger Christian Wohler Horst-Michael Gross Environment Perception DaimlerChrysler AG Group Research Ulm Germany Department of Neuroinformatics and Cognitive Robotics Technical University Ilmenau Ilmenau Germany

In this contribution we introduce the multiocular contracting curve density algorithm (MOCCD), a novel method for fitting a 3D parametric curve. The MOCCD is integrated into a tracking system and its suitability for tracking human body parts in 3D in front of cluttered background is examined. The developed system can be applied to a variety of body parts, as the object model is replaceable in a simple manner. Based on the example of tracking the human hand-forearm limb it is shown that the use of three MOCCD algorithms with three different kinematic models within the system leads to an accurate and temporally stable tracking. All necessary information is obtained from the images, only a coarse initialisation of the model parameters is required. The investigations are performed on 14 real-world test sequences. These contain movements of different hand-forearm configurations in front of a complex cluttered background. We find that the use of three cameras is essential for an accurate and temporally stable system performance since otherwise the pose estimation and tracking results are strongly affected by the aperture problem. Our best method achieves 95% recognition rate, compared to about 30% for the reference methods of 3D active contours and a curve model tracked by a particle filter. Hence only 5% of the estimated model points exceed a distance of 12 cm with respect to the ground truth, using the proposed method.

关键词： Humans Curve fitting Biological system modeling Kinematics Performance evaluation Testing Cameras System performance Apertures Active contours

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Integration of a sound source detection into a probabilistic-based multimodal approach for person detection and tracking

Integration of a sound source detection into a probabilistic...

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19. Fachgesprach Autonome Mobile Systeme, AMS 2005 - 19th Expert Discussion on Autonomous Mobile Systems, AMS 2005

作者： Brückmann, Robert Scheidig, Andrea Martin, Christian Gross, Horst-Michael Department of Neuroinformatics and Cognitive Robotics Ilmenau Technical University Germany

ISBN: (纸本)3540302913

Dealing with methods of Human-Robot-Interaction and using a real mobile robot, stable methods for people detection and tracking are fundamental features of such a system and require information from different sources. Based on an existing probability-based and multimodal approach for person detection and tracking, in this paper, we discuss the integration of a further sensory cue. This sensory cue is a sound source detection emerged from auditory information. Firstly, we discuss a newly developed approach for a sound source detection applied for a real world problem, dealing with the difficulty of reverberant environments. Secondly, we show a possible solution to integrate the sound source detection into the already existing person detection and tracking system applied for the mobile interaction robot HOROS working in a real office environment.

关键词： Human robot interaction

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There you go! - Estimating pointing gestures in monocular images for mobile robot instruction

There you go! - Estimating pointing gestures in monocular im...

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RO-MAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication

作者： Richarz, J. Martin, C. Scheidig, A. Gross, H.M. Intelligent Systems Group Robotics Research Institute University of Dortmund Germany Department of Neuroinformatics and Cognitive Robotics Ilmenau Technical University Germany

ISBN: (纸本)1424405653

In this paper, we present a neural architecture that is capable of estimating a target point from a pointing gesture, thus enabling a user to command a mobile robot to a specific position in his local surroundings by means of pointing. In this context, we were especially interested to determine whether it is possible to implement a target point estimator using only monocular images of low-cost webcams. The feature extraction is also quite straightforward: We use a gabor jet to extract the feature vector from the normalized camera images;and a cascade of Multi Layer Perceptron (MLP) Classifiers as estimator. The System was implemented and tested on our mobile robotic assistant HOROS. The results indicate that it is in fact possible to realize a pointing estimator using monocular image data, but further efforts are necessary to improve the accuracy and robustness of our approach. © 2006 IEEE.

关键词： Mobile robots

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Probabilistic Multi-modal People Tracker and Monocular Pointing Pose Estimator for Visual Instruction of Mobile Robot Assistants

Probabilistic Multi-modal People Tracker and Monocular Point...

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International Joint Conference on Neural Networks (IJCNN)

作者： H. Gross J. Richarz S. Mueller A. Scheidig C. Martin Department of Neuroinformatics and Cognitive Robotics Ilmenau Technical University Ilmenau Germany

In this paper, we present two important aspects of our human-robot communication interface which is being developed in the context of our long-term research framework PERSES dealing with the development of highly interactive mobile robotic assistants. First, we introduce a multi-modal people detection and tracking system, a fundamental prerequisite for the observation of a human interaction partner and his nonverbal instructions given by pointing poses, gestures, head pose and eye gaze. Based on this detection and tracking system, we present a hierarchical neural architecture that is capable of estimating a target point at the floor given a pointing pose, thus enabling a user to command his mobile robot to a specific target position in his local surroundings by means of pointing. In this context, we were especially interested in determining whether it is possible to accomplish such a target point estimator using only monocular images of low-cost cameras. Both the tracker and the target point estimator were implemented and experimentally investigated on our mobile robotic assistant HOROS. The achieved recognition results presented finally demonstrate that it is in fact possible to realize a user-independent pointing pose estimation using monocular images only, but further efforts are necessary to improve the robustness of this approach for everyday application.

关键词： Mobile robots Target tracking Mobile communication Context Human robot interaction Head Robot vision systems Cameras Image recognition Robustness

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A probabilistic multimodal sensor aggregation scheme applied for a mobile robot 1

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28th Annual German Conference on AI, KI 2005: Advances in Artificial Intelligence

作者： Schaffernicht, Erik Martin, Christian Scheidig, Andrea Gross, Horst-Michael Ilmenau Technical University Department of Neuroinformatics and Cognitive Robotics

ISBN: (数字)9783540318187

ISBN: (纸本)3540287612

Dealing with methods of human-robot interaction and using a real mobile robot, stable methods for people detection and tracking are fundamental features of such a system and require information from different sensory. In this paper, we discuss a new approach for integrating several sensor modalities and we present a multimodal people detection and tracking system and its application using the different sensory systems of our mobile interaction robot HOROS working in a real office environment. These include a laser-range-finder, a sonar system, and a fisheye-based omnidirectional camera. For each of these sensory information, a separate Gaussian probability distribution is generated to model the belief of the observation of a person. These probability distributions are further combined using a flexible probabilistic aggregation scheme. The main advantages of this approach are a simple integration of further sensory channels, even with different update frequencies and the usability in real-world environments. Finally, promising experimental results achieved in a real office environment will be presented. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Mobile robots

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Omniview-based concurrent map building and localization using adaptive appearance maps

Omniview-based concurrent map building and localization usin...

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IEEE Systems, Man and Cybernetics Society, Proceedings - 2005 International Conference on Systems, Man and Cybernetics

作者： Gross, H.-M. Koenig, A. Mueller, St Ilmenau Technical University Department of Neuroinformatics and Cognitive Robotics 98684 Ilmenau Germany

This paper describes a novel omnivision-based Concurrent Map-building and Localization (CML) approach which is able to robustly localize a mobile robot in a uniformly structured, maze-like environment with changing appearances. The presented approach extends and improves known appearance-based CML techniques in a few essential aspects. For example, an advanced learning scheme in combination with an active forgetting is introduced to allow a complexity restricting adaptation of the environment model to appearance variations of the operation area. Moreover, a generalized scheme for fusion of localization hypotheses from several state estimators with different meaning and certainty and a distributed coding of the current observation by a weighted set of reference observations is proposed. Finally, several real-world localization experiments investigating the stability and localization accuracy of this novel omnivision-based CML technique for a highly dynamic and populated operation area, a home store, are presented. © 2005 IEEE.

关键词： Adaptive control systems

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Neural architecture for concurrent map building and localization using adaptive appearance maps

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15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005

作者： Mueller, St. Koenig, A. Gross, H.-M. Department of Neuroinformatics and Cognitive Robotics Ilmenau Technical University 98684 Ilmenau Germany

ISBN: (纸本)3540287558

This paper describes a novel omnivision-based Concurrent Map-building and Localization (CML) approach which is able to localize a mobile robot in complex and dynamic environments. The approach extends or improves known CML techniques in essential aspects. For example, a more flexible model of the environment is used to represent experienced observations. By applying an improved learning regime, observations which are not longer of importance for the localization task are actively forgotten to limit complexity. Furthermore, a generalized scheme for hypotheses fusion is presented that enables the integration of further multi-sensory position estimators. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Neural networks

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Classification of face images for gender, age, facial expression, and identity

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15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005

作者： Wilhelm, Torsten Böhme, Hans-Joachim Gross, Horst-Michael Department of Neuroinformatics and Cognitive Robotics Ilmenau Technical University P.O. Box 100565 98684 Ilmenau Germany

ISBN: (纸本)3540287523

In this paper we compare two models for extracting features from face images and several neural classifiers for their applicability to classify gender, age, facial expression, and identity. These models are i) a description of face images by their projection on independent base images and ii) an Active Appearance Model which describes the shape and grey value variations of the face images. The extracted feature vectors are classified with Nearest Neighbor, MLP, RBF and LVQ networks, and classification results are compared. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Face recognition

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