Threading Fundamental Matrices
نویسندگان
چکیده
ÐWe present a new function that operates on Fundamental matrices across a sequence of views. The operation, we call athreadingo, connects two consecutive Fundamental matrices using the trifocal tensor as the connecting thread. The threading operation guarantees that consecutive camera matrices are consistent with a unique 3D model, without ever recovering a 3D model. Applications include recovery of camera ego-motion from a sequence of views, image stabilization (plane stabilization) across a sequence, and multiview image-
منابع مشابه
Enriching the sequence substitution matrix by structural information.
A fundamental step in homology modeling is the comparison of two protein sequences: a probe sequence with an unknown structure and function and a template sequence for which the structure and function are known. The detection of protein similarities relies on a substitution matrix that scores the proximity of the aligned amino acids. Sequence-to-sequence alignments use symmetric substitution ma...
متن کاملA Method for Determination of the Fundamental Period of Layered Soil Profiles
In this study, a method is proposed to determine the fundamental period of layered soil profiles. A model considering the layered soil as shear type structure is used. At first, the soil profile is divided into substructures. Then, the stiffness matrices of the substructures considered as the equivalent shear structures are assembled according to the Finite Element Method. Thereinafter, the sti...
متن کاملMultifrontral multithreaded rank-revealing sparse QR factorization
SuiteSparseQR is a sparse multifrontal QR factorization algorithm. Dense matrix methods within each frontal matrix enable the method to obtain high performance on multicore architectures. Parallelism across different frontal matrices is handled with Intel’s Threading Building Blocks library. Rank-detection is performed within each frontal matrix using Heath’s method, which does not require colu...
متن کاملComparison of Direct and Iterative Sparse Linear Solvers for Power System Applications on Parallel Computing Platforms
This paper presents a performance comparison of sparse linear solvers based on iterative and direct methods for power system applications implemented on parallel computing platform. The iterative sparse linear solver evaluated in this paper is based on the conjugate gradient algorithm with a Jacobi pre-conditioner executed on a general purpose graphic processing unit (GPGPU). The direct solvers...
متن کاملPerformance Comparison of Middleware Threading Strategies
The spectacular growth of E-business applications on the Internet has boosted the development of middleware technology. Middleware is software that manages interactions between applications distributed across a heterogeneous computing environment. In the competitive E-business market the ability to deliver a high and predictable performance of E-business applications is crucial to avoid custome...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1998