PoseGravity: Pose Estimation from Points and Lines with Axis Prior

• URL: http://arxiv.org/abs/2405.12646v2
• Date: Mon, 16 Sep 2024 21:58:00 GMT
• Title: PoseGravity: Pose Estimation from Points and Lines with Axis Prior
• Authors: Akshay Chandrasekhar,
• Abstract summary: This paper presents a new algorithm to estimate absolute camera pose given an axis of the camera's rotation matrix. The problem can be solved efficiently by finding the intersection points of a hyperbola and the unit circle.
• Score: 3.5687541347524245
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents a new algorithm to estimate absolute camera pose given an axis of the camera's rotation matrix. Current algorithms solve the problem via algebraic solutions on limited input domains. This paper shows that the problem can be solved efficiently by finding the intersection points of a hyperbola and the unit circle. The solution can flexibly accommodate combinations of point and line features in minimal and overconstrained configurations. In addition, the two special cases of planar and minimal configurations are identified to yield simpler closed-form solutions. Extensive experiments validate the approach.

Related papers

• SPARE: Symmetrized Point-to-Plane Distance for Robust Non-Rigid Registration [76.40993825836222]
  We propose SPARE, a novel formulation that utilizes a symmetrized point-to-plane distance for robust non-rigid registration. The proposed method greatly improves the accuracy of non-rigid registration problems and maintains relatively high solution efficiency.
  arXiv  Detail & Related papers  (2024-05-30T15:55:04Z)
• Relative pose of three calibrated and partially calibrated cameras from four points using virtual correspondences [56.44647186049448]
  We study challenging problems of estimating the relative pose of three cameras. Our solutions are based on the simple idea of generating one or two additional virtual point correspondences in two views.
  arXiv  Detail & Related papers  (2023-03-28T15:50:48Z)
• Convex mixed-integer optimization with Frank-Wolfe methods [20.37026309402396]
  Mixed-integer nonlinear optimization presents both theoretical and computational challenges. We propose a new type of method to solve these problems based on a branch-and-bound algorithm with convex node relaxations.
  arXiv  Detail & Related papers  (2022-08-23T14:46:54Z)
• Multiple Convex Objects Image Segmentation via Proximal Alternating Direction Method of Multipliers [2.294014185517203]
  The convex shape prior turns out to be a simple quadratic inequality constraint on the binary indicator function associated with each object. An image segmentation model incorporating convex shape prior into a probability-based method is proposed. Numerical experiments on natural and medical images demonstrate that the proposed method is superior to some existing methods.
  arXiv  Detail & Related papers  (2022-03-22T00:05:19Z)
• Coordinate Descent Methods for Fractional Minimization [7.716156977428555]
  We consider a class of structured fractional convex problems in which the numerator part objective is the sum of a differentiable convex non-linear function. This problem is difficult since it is non-smooth convergence. We propose two methods for solving this problem.
  arXiv  Detail & Related papers  (2022-01-30T00:47:04Z)
• Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation [71.27989298860481]
  We address the non- optimisation problem of finding a matrix on the Stiefel manifold that maximises a quadratic objective function. We propose a simple yet effective sparsity-promoting algorithm for finding the dominant eigenspace matrix.
  arXiv  Detail & Related papers  (2021-09-30T19:17:35Z)
• Calibrated and Partially Calibrated Semi-Generalized Homographies [65.29477277713205]
  We propose the first minimal solutions for estimating the semi-generalized homography given a perspective and a generalized camera. The proposed solvers are stable and efficient as demonstrated by a number of synthetic and real-world experiments.
  arXiv  Detail & Related papers  (2021-03-11T08:56:24Z)
• Hybrid Trilinear and Bilinear Programming for Aligning Partially Overlapping Point Sets [85.71360365315128]
  In many applications, we need algorithms which can align partially overlapping point sets are invariant to the corresponding corresponding RPM algorithm. We first show that the objective is a cubic bound function. We then utilize the convex envelopes of trilinear and bilinear monomial transformations to derive its lower bound. We next develop a branch-and-bound (BnB) algorithm which only branches over the transformation variables and runs efficiently.
  arXiv  Detail & Related papers  (2021-01-19T04:24:23Z)
• A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization [25.73397307080647]
  We present a new model of a general convex or non objective machine machine objectives. We propose an algorithm that solves a constraint with gradually relaxed point levels of each subproblem. We demonstrate the effectiveness of our new numerical scale problems.
  arXiv  Detail & Related papers  (2020-10-23T05:24:05Z)
• Conditional gradient methods for stochastically constrained convex minimization [54.53786593679331]
  We propose two novel conditional gradient-based methods for solving structured convex optimization problems. The most important feature of our framework is that only a subset of the constraints is processed at each iteration. Our algorithms rely on variance reduction and smoothing used in conjunction with conditional gradient steps, and are accompanied by rigorous convergence guarantees.
  arXiv  Detail & Related papers  (2020-07-07T21:26:35Z)
• A Unified Single-loop Alternating Gradient Projection Algorithm for Nonconvex-Concave and Convex-Nonconcave Minimax Problems [8.797831153231664]
  We develop an efficient algorithm for solving minimax problems with theoretical general convexnon objective guarantees. We show that the proposed algorithm can be used to solve both noncaveepsilon concave (strongly) and (strongly) convexnonconcave minimax problems.
  arXiv  Detail & Related papers  (2020-06-03T04:00:52Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.