MCMC-Based Multiview Reconstruction of Piecewise Smooth Subdivision Curves with a Variable Number of Control Points

2004 ◽  
pp. 329-341 ◽  
Author(s):  
Michael Kaess ◽  
Rafal Zboinski ◽  
Frank Dellaert
Keyword(s):  
Variable Number ◽  
Piecewise Smooth ◽  
Control Points ◽  
Subdivision Curves

scholarly journals Creases and boundary conditions for subdivision curves

2020 ◽  
Author(s):  
J Kosinka ◽  
M Sabin ◽  
Neil Dodgson
Keyword(s):  
Control Points ◽  
Knot Insertion ◽  
Degree Polynomial ◽  
Arbitrary Degree ◽  
B Splines ◽  
Novel Approach ◽  
Low Degree ◽  
Subdivision Curves ◽  
Subspace Selection ◽  
Subdivision Rules

Our goal is to find subdivision rules at creases in arbitrary degree subdivision for piece-wise polynomial curves, but without introducing new control points e.g. by knot insertion. Crease rules are well understood for low degree (cubic and lower) curves. We compare three main approaches: knot insertion, ghost points, and modifying subdivision rules. While knot insertion and ghost points work for arbitrary degrees for B-splines, these methods introduce unnecessary (ghost) control points. The situation is not so simple in modifying subdivision rules. Based on subdivision and subspace selection matrices, a novel approach to finding boundary and sharp subdivision rules that generalises to any degree is presented. Our approach leads to new higher-degree polynomial subdivision schemes with crease control without introducing new control points. © 2014 The Authors. Published by Elsevier Inc.

scholarly journals Creases and boundary conditions for subdivision curves

2021 ◽  
Author(s):  
J Kosinka ◽  
M Sabin ◽  
Neil Dodgson
Keyword(s):  
Control Points ◽  
Knot Insertion ◽  
Degree Polynomial ◽  
Arbitrary Degree ◽  
B Splines ◽  
Novel Approach ◽  
Low Degree ◽  
Subdivision Curves ◽  
Subspace Selection ◽  
Subdivision Rules

Our goal is to find subdivision rules at creases in arbitrary degree subdivision for piece-wise polynomial curves, but without introducing new control points e.g. by knot insertion. Crease rules are well understood for low degree (cubic and lower) curves. We compare three main approaches: knot insertion, ghost points, and modifying subdivision rules. While knot insertion and ghost points work for arbitrary degrees for B-splines, these methods introduce unnecessary (ghost) control points. The situation is not so simple in modifying subdivision rules. Based on subdivision and subspace selection matrices, a novel approach to finding boundary and sharp subdivision rules that generalises to any degree is presented. Our approach leads to new higher-degree polynomial subdivision schemes with crease control without introducing new control points. © 2014 The Authors. Published by Elsevier Inc.

scholarly journals Creases and boundary conditions for subdivision curves

2020 ◽  
Author(s):  
J Kosinka ◽  
M Sabin ◽  
Neil Dodgson
Keyword(s):  
Control Points ◽  
Knot Insertion ◽  
Degree Polynomial ◽  
Arbitrary Degree ◽  
B Splines ◽  
Novel Approach ◽  
Low Degree ◽  
Subdivision Curves ◽  
Subspace Selection ◽  
Subdivision Rules

Our goal is to find subdivision rules at creases in arbitrary degree subdivision for piece-wise polynomial curves, but without introducing new control points e.g. by knot insertion. Crease rules are well understood for low degree (cubic and lower) curves. We compare three main approaches: knot insertion, ghost points, and modifying subdivision rules. While knot insertion and ghost points work for arbitrary degrees for B-splines, these methods introduce unnecessary (ghost) control points. The situation is not so simple in modifying subdivision rules. Based on subdivision and subspace selection matrices, a novel approach to finding boundary and sharp subdivision rules that generalises to any degree is presented. Our approach leads to new higher-degree polynomial subdivision schemes with crease control without introducing new control points. © 2014 The Authors. Published by Elsevier Inc.

scholarly journals Creases and boundary conditions for subdivision curves

2021 ◽  
Author(s):  
J Kosinka ◽  
M Sabin ◽  
Neil Dodgson
Keyword(s):  
Control Points ◽  
Knot Insertion ◽  
Degree Polynomial ◽  
Arbitrary Degree ◽  
B Splines ◽  
Novel Approach ◽  
Low Degree ◽  
Subdivision Curves ◽  
Subspace Selection ◽  
Subdivision Rules

Our goal is to find subdivision rules at creases in arbitrary degree subdivision for piece-wise polynomial curves, but without introducing new control points e.g. by knot insertion. Crease rules are well understood for low degree (cubic and lower) curves. We compare three main approaches: knot insertion, ghost points, and modifying subdivision rules. While knot insertion and ghost points work for arbitrary degrees for B-splines, these methods introduce unnecessary (ghost) control points. The situation is not so simple in modifying subdivision rules. Based on subdivision and subspace selection matrices, a novel approach to finding boundary and sharp subdivision rules that generalises to any degree is presented. Our approach leads to new higher-degree polynomial subdivision schemes with crease control without introducing new control points. © 2014 The Authors. Published by Elsevier Inc.

Practical Realization of a Reference System for Earth Dynamics by Satellite Methods

1975 ◽  
Vol 26 ◽  
pp. 341-380 ◽  
Author(s):  
R. J. Anderle ◽  
M. C. Tanenbaum
Keyword(s):  
Reference Frame ◽  
Polar Motion ◽  
Pole Position ◽  
Control Points ◽  
Significant Information ◽  
Crustal Motion ◽  
Average Reference ◽  
Future Data ◽  
Existing Data

AbstractObservations of artificial earth satellites provide a means of establishing an.origin, orientation, scale and control points for a coordinate system. Neither existing data nor future data are likely to provide significant information on the .001 angle between the axis of angular momentum and axis of rotation. Existing data have provided data to about .01 accuracy on the pole position and to possibly a meter on the origin of the system and for control points. The longitude origin is essentially arbitrary. While these accuracies permit acquisition of useful data on tides and polar motion through dynamio analyses, they are inadequate for determination of crustal motion or significant improvement in polar motion. The limitations arise from gravity, drag and radiation forces on the satellites as well as from instrument errors. Improvements in laser equipment and the launch of the dense LAGEOS satellite in an orbit high enough to suppress significant gravity and drag errors will permit determination of crustal motion and more accurate, higher frequency, polar motion. However, the reference frame for the results is likely to be an average reference frame defined by the observing stations, resulting in significant corrections to be determined for effects of changes in station configuration and data losses.

Quantitative evaluation of post-bone marrow transplant engraftment status using fluorescent-labeled variable number of tandem repeats

2000 ◽  
Vol 05 (2) ◽  
pp. 129-138
Author(s):  
Robert A. Luhm ◽  
Daniel B. Bellissimo ◽  
Arejas J. Uzgiris ◽  
William R. Drobyski ◽  
Martin J. Hessner
Keyword(s):  
Bone Marrow ◽  
Bone Marrow Transplant ◽  
Quantitative Evaluation ◽  
Tandem Repeats ◽  
Marrow Transplant ◽  
Variable Number

On-farm udder health monitoring

2011 ◽  
Vol 39 (02) ◽  
pp. 95-100
Author(s):  
J. C. van Veersen ◽  
O. Sampimon ◽  
R. G. Olde Riekerink ◽  
T. J. G. Lam
Keyword(s):  
Management Practices ◽  
Health Management ◽  
Action Plan ◽  
Real Life ◽  
Health Data ◽  
Control Points ◽  
Udder Health ◽  
Critical Control Points ◽  
On Farm ◽  
Clinical Problems

SummaryIn this article an on-farm monitoring approach on udder health is presented. Monitoring of udder health consists of regular collection and analysis of data and of the regular evaluation of management practices. The ultimate goal is to manage critical control points in udder health management, such as hygiene, body condition, teat ends and treatments, in such a way that results (udder health parameters) are always optimal. Mastitis, however, is a multifactorial disease, and in real life it is not possible to fully prevent all mastitis problems. Therefore udder health data are also monitored with the goal to pick up deviations before they lead to (clinical) problems. By quantifying udder health data and management, a farm is approached as a business, with much attention for efficiency, thought over processes, clear agreements and goals, and including evaluation of processes and results. The whole approach starts with setting SMART (Specific, Measurable, Acceptable, Realistic, Time-bound) goals, followed by an action plan to realize these goals.

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