کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
529663 869693 2016 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
New iterative closest point algorithm for isotropic scaling registration of point sets with noise
ترجمه فارسی عنوان
الگوریتم نزدیک ترین نقطه تکرار جدید برای ثبت مقیاس ایزوتروپیک مجموعه های نقطه با نویز
کلمات کلیدی
نزدیکترین نقطه عطف، مقیاس محدود، ثبت نام نقطه، سر و صدا، مدل گاوسی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


• The one-to-one correspondence is adopted to accelerate the speed.
• The idea of from coarse to fine is employed to prevent local minimum.
• The proposed approach achieves fast speed and high accuracy.

This paper proposes a new probability iterative closest point (ICP) approach with bounded scale based on expectation maximization (EM) estimation for isotropic scaling registration of point sets with noise. The bounded-scale ICP algorithm can handle the case with different scales, but it could not effectively yield the alignment of point sets with noise. Aiming at improving registration precision, a Gaussian probability model is integrated into the bounded-scale registration problem, which is solved by the proposed method. This new method can be solved by the E-step and M-step. In the E-step, the one-to-one correspondence is built up between two point sets. In the M-step, the scale transformation including the rotation matrix, translation vector and scale factor is computed by singular value decomposition (SVD) method and the properties of parabola. Then, the Gaussian model is updated via the distance and variance between transformed point sets. Experimental results demonstrate the proposed method improves the performance significantly with high precision and fast speed.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 38, July 2016, Pages 207–216
نویسندگان
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