We focus on the problem of automatically extracting the 3D configuration of human poses from 2D image features tracked over a finite interval of time . This problem is highly non-linear in nature and confounds standar...
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ISBN:
(纸本)1901725340
We focus on the problem of automatically extracting the 3D configuration of human poses from 2D image features tracked over a finite interval of time . This problem is highly non-linear in nature and confounds standard regression techniques. Our approach effectively marries a non-rigid factorization algorithm with prior learned statistical models from archival motion capture database. We show that a stand alone non-rigid factorization algorithm is highly unsuitable for this problem. However, when coupled with the learned statistical model in the form of a constrained nonlinear programming method, it yields a substantially better solution.
Historically, natural disasters have been the cause of significant life and/or property losses. Every year, at least one state in the US suffers loss of lives and property damage due to hurricanes, wildfires, etc. Mor...
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Historically, natural disasters have been the cause of significant life and/or property losses. Every year, at least one state in the US suffers loss of lives and property damage due to hurricanes, wildfires, etc. More recently, the need for better emergency evacuation planning models increased significantly, especially in the aftermath of Hurricane Katrina. Most recently, several authorities state that there are weaknesses in the models that are currently employed in practice. We present an integer non-linear programming model that generates a response plan for emergency evacuation in the event of anticipated hurricanes. A computational example is provided.
We propose a new adaptive space deformation method for interactive shape modeling. A novel energy formulation based on elastically coupled volumetric cells yields intuitive detail preservation even under large deforma...
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We propose a new adaptive space deformation method for interactive shape modeling. A novel energy formulation based on elastically coupled volumetric cells yields intuitive detail preservation even under large deformations. By enforcing rigidity of the cells, we obtain an extremely robust numerical solver for the resulting nonlinear optimization problem. Scalability is achieved using an adaptive spatial discretization that is decoupled from the resolution of the embedded object. Our approach is versatile and easy to implement, supports thin-shell and solid deformations of 2D and 3D objects, and is applicable to arbitrary sample-based representations, such as meshes, triangle soaps, or point clouds.
In this contribution, the open-loop optimal control (dynamic optimization) of a Simulated Moving Bed (SMB) chromatographic separation process is considered. The objective is to compute the optimal feed concentration a...
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Most DiffServ admission control (AC) algorithms rely on tuning parameters to help in the decision making. Tuning these parameters is a difficult task, especially when one considers the problem of assuring QoS guarante...
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This work explores the use of a cooperative optimization algorithm, known as 'local pursuit', as a numerical tool for computing optimal control-trajectory pairs. Local pursuit is inspired by the foraging activ...
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A modern space mission is usually composed of several events such as impulsive maneuvers, thrust arcs, and flybys. Traditionally, a mission planner would develop a structure for the mission using categorical variables...
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ISBN:
(纸本)9780877035411
A modern space mission is usually composed of several events such as impulsive maneuvers, thrust arcs, and flybys. Traditionally, a mission planner would develop a structure for the mission using categorical variables, and then find the best spacecraft trajectory solving a continuous optimal control problem. A problem of this type involving categorical and continuous variables in the formulation is known as a hybrid optimal control (HOC) problem. A recent approach to solving HOC problems has the potential to automate the mission planning process by minimizing human intervention in the loop. The method uses two nested loops: an outer-loop which handles the finite dynamics and finds a solution sequence in terms of the categorical variables, and an inner-loop which performs the optimization of the continuous-time dynamical system and obtains the required control law. In this work, we introduce genetic algorithms and Runge-Kutta parallel-shooting with nonlinear programming as methods of solution for the outer-loop and inner-loop problems respectively.
Self-optimizing control is a promising method for finding appropriate controlled variables. Recently, locally optimal methods were introduced for finding controlled variables by minimizing the worst-case loss. In this...
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An optimization model was developed in conjunction with the perturbed finite element in order to achieve optimal desired cable performance. It considers various design parameters and sensitivities associated with thes...
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ISBN:
(纸本)9780889866218
An optimization model was developed in conjunction with the perturbed finite element in order to achieve optimal desired cable performance. It considers various design parameters and sensitivities associated with these parameters simultaneously and provides the optimal solution subject to user-defined constraints. The design problem of selecting the optimal parameter values of the thermal circuit parameters, including the thermal conductivities, boundary conditions and heat generation, is formulated using a multi-dimensional gradient optimization method. The technique considers all thermal circuit parameters and provides the optimal solution which minimizes the objective function. This model represents a generalization of the nonlinear programming formulation to include practical cases of the cable design objective functions which may include the thermal parameters and the cable temperatures (ampacity) subjected to upper and lower bounds on the design parameters, linear system of equations constrains, or nonlinear constrains. The optimization analysis includes the sensitivity profiles of the temperature (or ampacity) with respect to the thermal circuit parameters, or constraints other suitable objective functions so that a secure, reliable cable design may be obtained.
nonlinear Model Predictive Control (NMPC) algorithms are based on various nonlinear models. Recently, an on-line optimization approach for stochastic NMPC based on a Gaussian process model was proposed. A significant ...
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