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检索条件"任意字段=Conference on Sensor Fusion - Architectures, Algorithms, and Applications"

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A new pixel-based fusion framework to enhance object detection in automotive applications

A new pixel-based fusion framework to enhance object detecti...

引用

International conference on Information fusion

作者： Jan Thomanek Gerd Wanielik Ingenieurgesellschaft Auto und Verkehr GmbH Berlin Germany

ISBN: (纸本)9781479916344

Modern cooperative Advanced Driver Assistance Systems (ADASs) require efficient algorithms and methods for the real-time processing of all sensor data. In particular, systems for combination of different sensors are gaining increasing importance. This paper proposes an early fusion technique to combine the advantages of two or more vision sensors. It creates a single composite image that will be more comprehensive for further computer vision tasks, e.g. Object Detection. After image registration, the presented pixel-based fusion framework transforms the registered sensor images into a common representational format by a multiscale decomposition. A denoising and a multiscale edge detection are applied on the transformed data. Only data with a high Activity Level are considered for the fusion process that based on a probabilistic approach. Finally, the fused image can be the input for a subsequent feature extraction task. The proposed fusion technique is examined on a Pedestrian Detection System based on an infrared and a visible light camera.

关键词： Image edge detection Wavelet transforms Cameras Feature extraction Object detection Wavelet domain

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On nonlinear track-to-track fusion with Gaussian mixtures

On nonlinear track-to-track fusion with Gaussian mixtures

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International conference on Information fusion

作者： Benjamin Noack Marc Reinhardt Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Germany

The problem of fusing state estimates is encountered in many network-based multi-sensor applications. The majority of distributed state estimation algorithms are designed to provide multiple estimates on the same state, and track-to-track fusion then refers to the task of combining these estimates. While linear fusion only requires the joint cross-covariance matrix to be known, dependencies between estimates in nonlinear estimation problems have to be represented by high-dimensional probability density functions. In general, storing and keeping track of nonlinear dependencies is too cumbersome. However, this paper demonstrates that estimates represented by Gaussian mixtures prove to be an important exception to this rule. The dependency structure can as well be characterized in terms of a higher-dimensional Gaussian mixture. The different processing steps of distributed nonlinear state estimation, i.e., prediction, filtering, and fusion, are studied in light of the joint density representation. The presented concept is complemented with different simpler suboptimal representations of the dependency structure between Gaussian mixture densities.

关键词： Joints Barium Covariance matrices Noise Kalman filters State estimation

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Using trust in distributed consensus with adversaries in sensor and other networks

Using trust in distributed consensus with adversaries in sen...

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International conference on Information fusion

作者： Xiangyang Liu John S. Baras Institute for Systems Research University of Maryland College Park

ISBN: (纸本)9781479916344

Extensive research efforts have been devoted to distributed consensus with adversaries. Many diverse applications drive this increased interest in this area including distributed collaborative sensor networks, sensor fusion and distributed collaborative control. We consider the problem of detecting Byzantine adversaries in a network of agents with the goal of reaching consensus. We propose a novel trust model that establishes both local trust based on local evidences and global trust based on local exchange of local trust values. We describe a trust-aware consensus algorithm that integrates the trust evaluation mechanism into the traditional consensus algorithm and propose various local decision rules based on local evidence. To further enhance the robustness of trust evaluation itself, we also provide a trust propagation scheme in order to take into account evidences of other nodes in the network. The algorithm is flexible and extensible to incorporate more complicated designs of decision rules and trust models. Then we show by simulation that the trust-aware consensus algorithm can effectively detect Byzantine adversaries and excluding them from consensus iterations even in sparse networks with connectivity less than 2f + 1, where f is the number of adversaries. These results can be applied for fusion of trust evidences as well as for sensor fusion when malicious sensors are present like for example in power grid sensing and monitoring.

关键词： Peer-to-peer computing Mathematical model Equations Nickel Algorithm design and analysis Clustering algorithms Modeling

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Kinect based people identification system using fusion of clustering and classification

Kinect based people identification system using fusion of cl...

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International conference on Computer Vision Theory and applications (VISAPP)

作者： Aniruddha Sinha Diptesh Das Kingshuk Chakravarty Amit Konar Sudeepto Dutta Innovation Lab Tata Consultancy Services Ltd. Kolkata India Dept. of Electronics and Tele-communication Engineering Jadavpur University Kolkata India Sikkim Manipal Institute of Technology Sikkim India

ISBN: (纸本)9781479976867

The demand of human identification in a non-intrusive manner has risen increasingly in recent years. Several works have already been done in this context using gait-cycle detection from human skeleton data using Microsoft Kinect as a data capture sensor. In this paper we have proposed a novel method for automatic human identification in real time using the fusion of both supervised and unsupervised learning on gait-based features in an efficient way using Dempster-Shafer (DS) theory. Performance comparison of the proposed fusion based algorithm is done with that of the standard supervised or unsupervised algorithm and it needs to be mentioned that the proposed algorithm is able to achieve 71% recognition accuracy.

关键词： Clustering algorithms Feature extraction Support vector machines Hidden Markov models Hip Accuracy Training

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An accurate device for real-time altitude estimation using data fusion algorithms

An accurate device for real-time altitude estimation using d...

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IEEE/ASME International conference on Mechtronic and Embedded Systems and applications, MESA

作者： Paola Pierleoni Alberto Belli Lorenzo Palma Luca Pernini Simone Valenti Department of Information Engineering Marche Polytechnic University Ancona Italy

This paper presents an accurate system to estimate the altitude of a rigid body by fusing data from four low-cost sensors such as an accelerometer, a gyroscope, a magnetometer and an altimeter. Usually a MEMS altimeter barometric sensor allows to obtain the altitude signal from measures of atmospheric pressure and temperature but these measures are affected by noise that causes a significant error in the calculated altitude values. In order to get an accurate estimation of the altitude, in this work a complementary filter is used to fuse the raw signal of the altitude obtained from barometer sensor and vertical displacement signal calculated through a data fusion algorithm applied to the signals of the other three sensors. In order to evaluate the performance in human activity monitoring applications, the proposed device has been tested and compared with the system that currently presents the better performance for the same technology according to its experimental protocols. The results show that our device exceeds the performance provided by the currently systems reported in literature.

关键词： Acceleration Temperature measurement Estimation Earth Magnetic sensors Noise

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Energy Expenditure Prediction Algorithm Based on Correlation Analysis of Exercise Indexes

Energy Expenditure Prediction Algorithm Based on Correlation...

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International conference on Information Science and applications (ICISA)

作者： Kyeung Ho Kang Youn Tae Kim IT Fusion Technology Research Center Chosun University Gwangju Korea

This study proposes an energy expenditure prediction algorithm (EEPA) to predict the exact energy expended during different types of exercises. The EEPA uses relational expressions obtained through the correlation analysis of exercise indexes on ten types of exercises. The relational expression and algorithm indicated changes in energy expenditures according to the heart rates and movement intensity in each exercise. The movement indexes were measured according to the order, time, and intensity of each exercise with the help of a Wireless patch type sensor (AIRBEAT System). The results of the test were verified through a comparison and an analysis by AIRBEAT system and a wireless gas analyzer. The estimated energy expenditure using EEPA had a difference of less than 1% as compared to the actual results.

关键词： Heart rate Presses Indexes Prediction algorithms Algorithm design and analysis Wireless sensor networks Energy measurement

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2D and 3D image stabilization for robotic beating heart surgery

2D and 3D image stabilization for robotic beating heart surg...

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International conference on Information fusion

作者： Gerhard Kurz Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Karlsruhe Institute of Technology (KIT) Germany

ISBN: (纸本)9781479916344

Image stabilization is relevant for various industrial and medical applications. In particular, we consider the use of image stabilization in robotic beating heart surgery. A robot, which is remotely controlled by the surgeon, can automatically compensate for the motion of the beating heart. To give the surgeon the illusion of operating on a stationary heart, a stabilized image of the beating heart is shown to the surgeon. Image stabilization cancels the unwanted motion of the heart, but retains changes to color and texture, for example cuts on the heart surface. In this paper, stabilization is first considered as a 2D image transformation problem. Subsequently, it is extended to stabilization of a 3D point cloud or surface. The proposed algorithms are evaluated in both ex-vivo and in-vivo experiments. In the evaluation, the stabilization quality achievable with several common interpolation functions is compared.

关键词： Heart Three-dimensional displays Interpolation Cameras Surgery Splines (mathematics) Surface reconstruction

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UNCERTAINTY MODELING FOR EFFICIENT VISUAL ODOMETRY VIA INERTIAL sensorS ON MOBILE DEVICES

UNCERTAINTY MODELING FOR EFFICIENT VISUAL ODOMETRY VIA INERT...

引用

IEEE International conference on Image Processing

作者： Yagiz Aksoy A. Aydin Alatan Dept. of Electrical and Electronics Engineering Middle East Technical University

ISBN: (纸本)9781479957521

Most of the mobile applications require efficient and precise computation of the device pose, and almost every mobile device has inertial sensors already equipped together with a camera. This fact makes sensor fusion quite attractive for increasing efficiency during pose tracking. However, the state-of-the-art fusion algorithms have a major shortcoming: lack of well-defined uncertainty introduced to the system during the prediction stage of the fusion filters. Such a drawback results in determining covariances heuristically, and hence, requirement for data-dependent tuning to achieve high performance or even convergence of these filters. In this paper, we propose an inertially-aided visual odometry system that requires neither heuristics nor parameter tuning;computation of the required uncertainties on all the estimated variables are obtained after minimum number of assumptions. Moreover, the proposed system simultaneously estimates the metric scale of the pose computed from a monocular image stream. The experimental results indicate that the proposed scale estimation outperforms the state-of-the-art methods, whereas the pose estimation step yields quite acceptable results in real-time on resource constrained systems.

关键词： sensor fusion Inertial sensors Visual Odometry Pose Tracking Mobile Vision

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Non-linear compensation of production inaccuracies and material drift by adjusting the sensor data fusion algorithms for shape sensing based on FBG-optical fibers

Non-linear compensation of production inaccuracies and mater...

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International conference on Multisensor fusion and Integration for Intelligent Systems (MFI)

作者： Hendrikje Pauer Christoph Ledermann Wilderich Tuschmann Heinz Woern Institute for Anthropomatics and Robotics Intelligent Process Control and Robotics-Karlsruhe Institute of Technology Karlsruhe Germany Institute for Algebra and Geometry-Karlsruhe Institute of Technology Karlsruhe Germany

Shape sensing, where the shape of an object is estimated using fiber optical Fiber Bragg Grating (FBG) sensors, has gained increasing popularity in the last years. While the production process and the applications are different for the various research groups, the basic principle of shape sensing is the same: at certain cross-sections along the observed object, the information of three strain measurements is merged to one curvature information, and the information of these curvatures is then used to estimate the shape with various mathematical theories, depending on the application. Some effort has been made to calibrate and determine the accuracy of the shape sensor, but research on the influence of bad positioning of the Fiber Bragg Gratings seems relatively unattended. In this paper, one aspect of bad FBG positioning, namely inaccurate placement of the FBGs within one cross-section, and its influence on the reconstruction results is investigated. Furthermore, a modified approach for the reconstruction algorithm is presented, improving the reconstruction results for bad FBG placement compared to the conventional approach.

关键词： Shape Gratings Fiber gratings Robot sensing systems Strain

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An Efficient Approach to Node Localisation and Tracking in Wireless sensor Networks

An Efficient Approach to Node Localisation and Tracking in W...

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IEEE Global Communications conference

作者： Martin K. Mwila Karim Djouani Anish Kurien F'SATI/TUT Pretoria South Africa Tshwane University of Technology CSIR F'SATI/TUT Pretoria South Africa Tshwane University of Technology

ISBN: (纸本)9781479935130

Localisation is one of the most important applications for wireless sensor networks since the locations of the sensor nodes are critical to both network operations and most application level tasks. Numerous techniques for localisation of sensor nodes that make use of the Received Signal Strength Indicator (RSSI) have been proposed because of the simplicity and low cost of implementation. However, most of the research thus far has regarded the RSSI technology as unsuitable for accurate localisation due to the limited accuracy inherent to the current ranging models. These models make the assumption that the antenna radiation pattern is omnidirectional in order to simplify the complexity of the algorithms. In this study, an accurate and efficient localisation method that makes use of an improved RSSI distance estimation model by including the antenna radiation pattern as well as nodes orientations is presented. Mathematical models for distance estimation, cost function and gradient of cost function, that can be used in a distributed localisation algorithm, are developed. This study also introduces a sensor data fusion approach, combining accelerometer data, RSSI, antenna radiation pattern and node orientation to reduce the computation complexity during the tracking phase. The proposed algorithm is implemented in Matlab. Simulation results show that the proposed approach increases the accuracy of existing methods using RSSI by up to 59%.

关键词： Antenna Radiation Pattern Node Localisation sensor Data fusion Gauss-Newton Optimisation Method

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