Convex hull indexed Gaussian mixture model (CH-GMM) for 3D point set registration

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Bi-Stage Large Point Set Registration Using Gaussian Mixture Models

Point set registration is to determine correspondences between two different point sets, then recover the spatial transformation between them. Many current methods, become extremely slow as the cardinality of the point set increases; making them impractical for large point sets. In this paper, we propose a bi-stage method called bi-GMMTPS, based on Gaussian Mixture Models and Thin-Plate Splines...

متن کامل

Computing the convex hull of a planar point set

In Figure 1, the set S consists of thirteen points. The output of a convex hull algorithm should be the list (p1, p2, p3, p4, p5, p6). We remark that the list storing the vertices of CH (S) can start with an arbitrary vertex. In the example, the list (p3, p4, p5, p6, p1, p2) would also be a valid output. ∗School of Computer Science, Carleton University, Ottawa, Ontario, Canada K1S 5B6. E-mail: ...

متن کامل

Dependent landmark drift: robust point set registration based on the Gaussian mixture model with a statistical shape model

The goal of point set registration is to find point-by-point correspondences between point sets, each of which characterizes the shape of an object. Because local preservation of object geometry is assumed, prevalent algorithms in the area can often elegantly solve the problems without using geometric information specific to the objects. This means that registration performance can be further i...

متن کامل

Dependent landmark drift: robust point set registration with a Gaussian mixture model and a statistical shape model

The goal of point set registration is to find point-by-point correspondences between point sets, each of which characterizes the shape of an object. Because local preservation of object geometry is assumed, prevalent algorithms in the area can often elegantly solve the problems without using geometric information specific to the objects. This means that registration performance can be further i...

متن کامل

The Approach of Speaker Diarization by Gaussian Mixture Model (GMM)

Speaker identification is an important activity in the process of speaker diarization. We need to model the speaker by Gaussian mixture model (GMM) for speaker identification purpose. Large GMM is called as a Universal Background Model (UBM) which is adapted into each speaker model for speaker identification purpose. This paper focuses on speech clustering for speaker diarization. The speaker d...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Pattern Recognition

سال: 2016

ISSN: 0031-3203

DOI: 10.1016/j.patcog.2016.02.023