A simple and effective algorithm is Proposed for calibrating the extrinsic parameters among a camera and dual laser range sensors whose traces are invisible by using a specially designed checkerboard. On the basis of ...
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ISBN:
(纸本)9781424453603
A simple and effective algorithm is Proposed for calibrating the extrinsic parameters among a camera and dual laser range sensors whose traces are invisible by using a specially designed checkerboard. On the basis of an analysis of reference coordinates, range data can be transformed into world coordinate, and then a linear solution can be obtained for the problem. The simulation results confirmed that the proposed algorithm can yield good results as compared with a typical calibration method.
Touch screen phone roaming with people features high accessibility and direct-manipulation interaction, regarded as one of the most convenient interfaces for daily life. In this paper, we present HouseGenie to leverag...
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Touch screen phone roaming with people features high accessibility and direct-manipulation interaction, regarded as one of the most convenient interfaces for daily life. In this paper, we present HouseGenie to leverage universal monitor and control of networked devices in smart home on touch screen phone. By wirelessly communicating with an OSGi based portal, which maintains all the devices through varied protocols (e.g. industrial standard UPnP or IGRS), HouseGenie facilitates universal home monitor and control: 1) monitoring current status in panoramic view; 2) direct manipulating single/multiple device(s) using pie-menu, list-mode and drag drop gesture; 3) easily controlling devices in several multimodality ways.
To solve the problem of modeling the horizontal translational motion of a Raptor30 based miniature helicopter near hovering, a black-box model is built based on echo state networks. Combined with a state space angular...
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To solve the problem of modeling the horizontal translational motion of a Raptor30 based miniature helicopter near hovering, a black-box model is built based on echo state networks. Combined with a state space angular motion model, a four-degree-of-freedom hybrid model is created. System identification is done using the remote control experiment data. Model validation results demonstrate that the model can predict the motion of the miniature helicopter near hovering on the whole. The model can be used to optimize parameterized controller. Closed-loop simulation further validates the model.
This review explores recent trends in the development and evaluation of assistive robotic arms, both prosthetic and externally mounted. Evaluations have been organized according to the CATOR taxonomy of assistive devi...
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Dictionary generation is a core technique of the bag-of-visual-words (BOV) models when applied to image categorization. Most of previous approaches generate dictionaries by unsupervised clustering techniques, e.g. k-m...
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Dictionary generation is a core technique of the bag-of-visual-words (BOV) models when applied to image categorization. Most of previous approaches generate dictionaries by unsupervised clustering techniques, e.g. k-means. However, the features obtained by such kind of dictionaries may not be optimal for image classification. In this paper, we propose a probabilistic model for supervised dictionary learning (SDLM) which seamlessly combines an unsupervised model (a Gaussian Mixture Model) and a supervised model (a logistic regression model) in a probabilistic framework. In the model, image category information directly affects the generation of a dictionary. A dictionary obtained by this approach is a trade-off between minimization of distortions of clusters and maximization of discriminative power of image-wise representations, i.e. histogram representations of images. We further extend the model to incorporate spatial information during the dictionary learning process in a spatial pyramid matching like manner. We extensively evaluated the two models on various benchmark dataset and obtained promising results.
In this paper, we propose a new service platform which provides stable QoS by allocating components dynamically with considering fault-tolerance. We assume that many kinds of components are running on component server...
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In this paper, we propose a new service platform which provides stable QoS by allocating components dynamically with considering fault-tolerance. We assume that many kinds of components are running on component servers and each component has its own SLA. The proposed platform achieves to make a load-balancing system to meet SLA of these components SLA and considering the number of replications necessary to offer a continuous service in case of failure. Finally, by implementation of its prototyping system, we confirm that the proposed platform is effective and feasible to provide the network services based on distributed components.
In this paper, we present a visual object tracker for mobile systems that is able to specialize to individual objects during tracking. The core of our method is a novel observation model and the way it is automaticall...
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In this paper, we present a visual object tracker for mobile systems that is able to specialize to individual objects during tracking. The core of our method is a novel observation model and the way it is automatically adapted to a changing object and background appearance over time. The model is integrated into the well known Condensation algorithm (SIR filter) for statistical inference, and it consists of a boosted ensemble of simple threshold classifiers built upon center-surround Haar-like features, which the filter continuously updates based on the images perceived. We present optimizations and reasonable approximations to limit the computational costs. Thus, the final algorithms are capable of processing video input at real-time. To experimentally investigate the gain of adapting the observation model we compare two different approaches with a non-adapting version of our observation model: maintaining a single observation model for all particles, and maintaining individual observation models for each particle. In addition, experiments were conducted to compare system performances between the proposed algorithms and two other state of the art Condensation based tracking approaches.
A novel fault diagnostics and prediction scheme in continuous-time is introduced for a class of nonlinear systems. The proposed method uses a novel neural network (NN) based robust integral sign of the error (RISE) ob...
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A novel fault diagnostics and prediction scheme in continuous-time is introduced for a class of nonlinear systems. The proposed method uses a novel neural network (NN) based robust integral sign of the error (RISE) observer, or estimator, allowing for semi-global asymptotic stability in the presence of NN approximation errors, disturbances and unmodeled dynamics. This is in comparison to typical results presented in the literature that show only boundedness in the presence of uncertainties. The output of the observer/estimator is compared with that of the nonlinear system and a residual is used for declaring the presence of a fault when the residual exceeds a user defined threshold. The NN weights are tuned online with no offline tuning phase. The output of the RISE observer is utilized for diagnostics. Additionally, a method for time-to-failure (TTF) prediction, a first step in prognostics, is developed by projecting the developed parameter-update law under the assumption that the nonlinear system satisfies a linear-in-the-parameters (LIP) assumption. The TTF method uses known critical values of a system to predict when an estimated parameter will reach a known failure threshold. The performance of the NN/RISE observer system is evaluated on a nonlinear system and a simply supported beam finite element analysis (FEA) simulation based on laboratory experiments. Results show that the proposed method provides as much as 25% increased accuracy while the TTF scheme renders a more accurate prediction.
In order to get the acceleration, angular velocity and other kinematic parameters of the ski athlete during the training timely, which can help team coach analyse the action and guide the team members training with pu...
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