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estimates

  • The problem of image registration subsumes a number of problems and techniques in multiframe image

    The problem of image registration subsumes a number of problems and techniques in multiframe image analysis, including the computation of optic flow (general pixel-based motion), stereo correspondence, structure from motion, and feature tracking. We present a new registration algorithm based on spline representations of the displacement field which can be specialized to solve all of the above mentioned problems. In particular, we show how to compute local flow, global (parametric) flow, rigid flow resulting from camera egomotion, and multiframe versions of the above problems. Using a spline-based description of the flow removes the need for overlapping correlation windows, and produces an explicit measure of the correlation between adjacent flow estimates. We demonstrate our algorithm on multiframe image registration and the recovery of 3D projective scene geometry. We also provide results on a number of standard motion sequences.

    标签: image registration multiframe techniques

    上传时间: 2016-01-20

    上传用户:520

  • % EM algorithm for k multidimensional Gaussian mixture estimation % % Inputs: % X(n,d) - input da

    % EM algorithm for k multidimensional Gaussian mixture estimation % % Inputs: % X(n,d) - input data, n=number of observations, d=dimension of variable % k - maximum number of Gaussian components allowed % ltol - percentage of the log likelihood difference between 2 iterations ([] for none) % maxiter - maximum number of iteration allowed ([] for none) % pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) % Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) % % Ouputs: % W(1,k) - estimated weights of GM % M(d,k) - estimated mean vectors of GM % V(d,d,k) - estimated covariance matrices of GM % L - log likelihood of estimates

    标签: multidimensional estimation algorithm Gaussian

    上传时间: 2013-12-02

    上传用户:我们的船长

  • This approach addresses two difficulties simultaneously: 1) the range limitation of mobile robot se

    This approach addresses two difficulties simultaneously: 1) the range limitation of mobile robot sensors and 2) the difficulty of detecting buildings in monocular aerial images. With the suggested method building outlines can be detected faster than the mobile robot can explore the area by itself, giving the robot an ability to “see” around corners. At the same time, the approach can compensate for the absence of elevation data in segmentation of aerial images. Our experiments demonstrate that ground-level semantic information (wall estimates) allows to focus the segmentation of the aerial image to find buildings and produce a ground-level semantic map that covers a larger area than can be built using the onboard sensors.

    标签: simultaneously difficulties limitation addresses

    上传时间: 2014-06-10

    上传用户:waitingfy

  • documentation for optimal filtering toolbox for mathematical software package Matlab. The methods i

    documentation for optimal filtering toolbox for mathematical software package Matlab. The methods in the toolbox include Kalman filter, extended Kalman filter and unscented Kalman filter for discrete time state space models. Also included in the toolbox are the Rauch-Tung-Striebel and Forward-Backward smoother counter-parts for each filter, which can be used to smooth the previous state estimates, after obtaining new measurements. The usage and function of each method are illustrated with five demonstrations problems. 1

    标签: documentation mathematical for filtering

    上传时间: 2014-01-20

    上传用户:changeboy

  • documentation for optimal filtering toolbox for mathematical software package Matlab. The methods i

    documentation for optimal filtering toolbox for mathematical software package Matlab. The methods in the toolbox include Kalman filter, extended Kalman filter and unscented Kalman filter for discrete time state space models. Also included in the toolbox are the Rauch-Tung-Striebel and Forward-Backward smoother counter-parts for each filter, which can be used to smooth the previous state estimates, after obtaining new measurements. The usage and function of each method are illustrated with five demonstrations problems. 1

    标签: documentation mathematical for filtering

    上传时间: 2013-12-10

    上传用户:zxc23456789

  • GSM (Global System for Mobile communications: originally from Groupe Spécial Mobile) is the most pop

    GSM (Global System for Mobile communications: originally from Groupe Spécial Mobile) is the most popular standard for mobile phones in the world. Its promoter, the GSM Association, estimates that 80 of the global mobile market uses the standard.[1] GSM is used by over 3 billion people across more than 212 countries and territories.[2][3] Its ubiquity makes international roaming very common between mobile phone operators, enabling subscribers to use their phones in many parts of the world

    标签: Mobile communications originally Global

    上传时间: 2017-07-15

    上传用户:电子世界

  • sba, a C/C++ package for generic sparse bundle adjustment is almost invariably used as the last step

    sba, a C/C++ package for generic sparse bundle adjustment is almost invariably used as the last step of every feature-based multiple view reconstruction vision algorithm to obtain optimal 3D structure and motion (i.e. camera matrix) parameter estimates. Provided with initial estimates, BA simultaneously refines motion and structure by minimizing the reprojection error between the observed and predicted image points.

    标签: adjustment invariably package generic

    上传时间: 2013-12-18

    上传用户:xsnjzljj

  • Space-Time+Processing+for+Wireless+Communications

    In this thesis several asp ects of space-time pro cessing and equalization for wire- less communications are treated. We discuss several di?erent metho ds of improv- ing estimates of space-time channels, such as temp oral parametrization, spatial parametrization, reduced rank channel estimation, b o otstrap channel estimation, and joint estimation of an FIR channel and an AR noise mo del. In wireless commu- nication the signal is often sub ject to intersymb ol interference as well as interfer- ence from other users. 

    标签: Communications Space-Time Processing Wireless for

    上传时间: 2020-05-31

    上传用户:shancjb