منابع مشابه
Object Pose from D to D Point and Line Correspondences
In this paper we present a method for optimally estimating the rotation and transla tion between a camera and a D object from point and or line correspondences First we devise an error function and second we show how to minimize this error function The quadratic nature of this function is made possible by representing rotation and translation with a dual number quaternion We provide a detailed ...
متن کاملReconstruction of 3-D Figure Motion from 2-D Correspondences
We present a method for computing the 3D motion of articulated models from 2D correspondences. An iterative batch algorithm is proposed which estimates the maximum aposteriori trajectory based on the 2D measurements subject to a number of constraints. These include (i) kinematic constraints based on a 3D kinematic model, (ii) joint angle limits, (iii) dynamic smoothing and (iv) 3D key frames wh...
متن کاملPose Estimation using Point and Line Correspondences
The problem of object pose from 2D to 3D correspondences has received a lot of attention both in the photogrammetry and computer vision literatures. Various approaches to the object pose (or external camera parameters) problem fall into two distinct categories: closed-form solutions and non-linear solutions. Closed-form solutions may be applied only to a limited number of correspondences [1,2]....
متن کاملSubmitted to Pattern Recognition New Algorithms for 2 D and 3 D Point Matching : Pose Estimation
A fundamental open problem in computer vision|determining pose and correspondence between two sets of points in space|is solved with a novel, fast O(nm)], robust and easily implementable algorithm. The technique works on noisy 2D or 3D point sets that may be of unequal sizes and may diier by non-rigid transformations. Using a combination of optimization techniques such as deterministic annealin...
متن کاملA Feature Map Approach to Real-Time 3-D Object Pose Estimation from Single 2-D Perspective Views
A novel approach to the computation of an approximate estimate of spatial object pose from camera images is proposed. The method is based on a neural network that generates pose hypotheses in real time, which can be refined by registration or tracking systems. A modification of Kohonen’s self-organizing feature map is systematically trained with computer generated object views such that it resp...
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ژورنال
عنوان ژورنال: International Journal of Computer Vision
سال: 1995
ISSN: 0920-5691,1573-1405
DOI: 10.1007/bf01451742