The Experts below are selected from a list of 959910 Experts worldwide ranked by ideXlab platform
Li Bai - One of the best experts on this subject based on the ideXlab platform.
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real time probabilistic covariance tracking with Efficient Model update
IEEE Transactions on Image Processing, 2012Co-Authors: Jian Cheng, Jinqiao Wang, Jun Wang, Haibin Ling, Erik Blasch, Li BaiAbstract:The recently proposed covariance region descriptor has been proven robust and versatile for a modest computational cost. The covariance matrix enables Efficient fusion of different types of features, where the spatial and statistical properties, as well as their correlation, are characterized. The similarity between two covariance descriptors is measured on Riemannian manifolds. Based on the same metric but with a probabilistic framework, we propose a novel tracking approach on Riemannian manifolds with a novel incremental covariance tensor learning (ICTL). To address the appearance variations, ICTL incrementally learns a low-dimensional covariance tensor representation and Efficiently adapts online to appearance changes of the target with only computational complexity, resulting in a real-time performance. The covariance-based representation and the ICTL are then combined with the particle filter framework to allow better handling of background clutter, as well as the temporary occlusions. We test the proposed probabilistic ICTL tracker on numerous benchmark sequences involving different types of challenges including occlusions and variations in illumination, scale, and pose. The proposed approach demonstrates excellent real-time performance, both qualitatively and quantitatively, in comparison with several previously proposed trackers.
T. Blaszka - One of the best experts on this subject based on the ideXlab platform.
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CVPR - Recovering and characterizing image features using an Efficient Model based approach
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 1Co-Authors: Rachid Deriche, T. BlaszkaAbstract:The development of an Efficient Model-based approach to detect and characterize precisely important features such as edges, corners and vertices is discussed. The key is to propose some Efficient Models associated to each of these features directly from the image by searching the parameters of the Model that best approximate the observed grey level image intensities. Due to the large amount of time required by a first approach that assumes the blur of the imaging acquisition system to be describable by a 2-D Gaussian filter, different solutions that drastically reduce this computational time are considered and developed. The problem of the initialization phase in the minimization process is considered, and an original and Efficient solution is proposed. A large number of experiments involving real images are conducted in order to test and compare the reliability, the robustness, and the efficiency of the proposed approaches. >
Boris Rohal’-ilkiv - One of the best experts on this subject based on the ideXlab platform.
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ECC - Newton-raphson based Efficient Model predictive control applied on active vibrating structures
2009 European Control Conference (ECC), 2009Co-Authors: Gergely Takács, Boris Rohal’-ilkivAbstract:This article presents a computationally Efficient Model predictive algorithm, applied on an actively controlled vibrating structure. A brief introduction on the experimental device and theoretical background is followed by an analysis of the practical properties, drawbacks and performance of the controller in question. The experimental data presented and interpreted here shows, that the Newton-Raphson based predictive algorithm presents a viable approach to the control of fast sampling systems.
Wanming Zhai - One of the best experts on this subject based on the ideXlab platform.
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An Efficient Model for vehicle-slab track coupled dynamic analysis considering multiple slab cracks
Construction and Building Materials, 2019Co-Authors: Wanming ZhaiAbstract:Abstract This paper presents an Efficient Model for vehicle-slab track coupled dynamic analysis addressing the challenge problem of multiple slab cracks in high-speed railways. The multi-cracked track slabs are described as free Euler-Bernoulli beams supported on the cement asphalt (CA) mortar. The concentrated cracks are assumed to be in the through-transverse form, which are considered to locally affect the vertical bending stiffness of the beam and treated by applying the uniform flexural stiffness with Dirac’s delta singularities. The introduced damage parameters are expressed by incorporating the rotational springs using the linear elastic fracture mechanics. The vibration equations of slab track subsystem involving multiple slab cracks are finally set up by adopting the modal superposition approach, and are coupled with vehicle subsystem motions through nonlinear wheel-rail contact forces. An explicit integration method is applied to solve the whole coupled system excited by the random track irregularities. The developed Model can also be expediently degenerated to the traditional Model with intact slabs by setting the damage parameters to zero. Time-frequency analysis is conducted through fully investigating the effect of the crack depth, the crack numbers with different distribution properties and the CA mortar stiffness on the system dynamic responses. Some practical conclusions are drawn and may provide potent information for the maintenance in railway engineering and vibration based damage identification.
Albert Rosich - One of the best experts on this subject based on the ideXlab platform.
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Design and simulation of a real-time implementable energy-Efficient Model-predictive cruise controller for electric vehicles
Journal of The Franklin Institute, 2015Co-Authors: Tim Schwickart, Holger Voos, Mohamed Darouach, Jean-régis Hadji-minaglou, Albert RosichAbstract:This paper presents the design of a novel energy-Efficient Model-predictive cruise controller for electric vehicles as well a simulation Model of the longitudinal vehicle dynamics and its energy consumption. Both, the controller and the dynamic Model are designed to meet the properties of a series-production electric vehicle whose characteristics are identified and verified by measurements. A predictive eco-cruise controller involves the minimisation of a compromise between terms related to driving speed and energy consumption which are in general both described by nonlinear differential equations. Considering the nonlinearities is essential for a proper prediction of the system states over the prediction horizon to achieve the desired energy-saving behaviour. In this work, the vehicle motion equation is reformulated in terms of the kinetic energy of the moving vehicle which leads to a linear differential equation without loss of information. The energy consumption is Modeled implicitly by exploiting the special form of the optimisation problem. The reformulations finally lead to a Model-predictive control approach with quadratic cost function, linear prediction Model and linear constraints that corresponds to a piecewise linear system behaviour and allows a fast real-time implementation with guaranteed convergence. Simulation results of the MPC controller and the simulation Model in closed-loop operation finally provide a proof of concept.
