Real-Time Deformation of Subdivision Surfaces on Object Collisions

GPU Pro 360 ◽  
2018 ◽  
pp. 247-270
Author(s):  
Henry Schäfer ◽  
Matthias Nießner ◽  
Benjamin Keinert ◽  
Marc Stamminger
2020 ◽  
Vol 39 (6) ◽  
pp. 19-32
Author(s):  
F. Corda ◽  
J. M. Thiery ◽  
M. Livesu ◽  
E. Puppo ◽  
T. Boubekeur ◽  
...  
Keyword(s):  

2021 ◽  
Vol 26 (3) ◽  
pp. 290-297
Author(s):  
Mengjie Jing ◽  
Zhixin Cui ◽  
Hang Fu ◽  
Xiaojun Chen

2017 ◽  
Vol 209 (3) ◽  
pp. 1408-1417 ◽  
Author(s):  
Rui Tu ◽  
Jinhai Liu ◽  
Cuixian Lu ◽  
Rui Zhang ◽  
Pengfei Zhang ◽  
...  

Author(s):  
Hong-Il Kim ◽  
Lae-Hyong Kang ◽  
Jae-Hung Han

Dimensional stability of the space structures, such as large telescope mirrors or metering substructures, is very important because even extremely small deformations of these structures might degrade the optical performances. Therefore, precise deformation data of the space structures according to environment change are required to design these structures correctly. Also, real-time deformation monitoring of these structures in space environment is demanded to verify whether these structures are properly designed or manufactured. FBG (fiber Bragg grating) sensors are applicable to real time monitoring of the space structure because they can be embedded onto the structures with minimal weight penalty. In this research, therefore, thermal deformation measurement system for the space structures, composed of FBG sensors for real time strain measurement and DMI (displacement measuring interferometers) for accurate specimen expansion data acquisition, is developed. Thermal strains measured by distributed FBG sensors are evaluated by the comparison with the strains obtained by highly accurate DMI.


2011 ◽  
Vol 130-134 ◽  
pp. 3572-3576
Author(s):  
Li Zong Lin ◽  
Xiao Peng Ni ◽  
Luo Shan Zhou ◽  
Zhi Qin Qian

Dynamic deformation measurement of machine parts in fatigue strength test is studied by using machine vision technique. Considering the uncertainty of parts surface, we adopt circular mark to locate the object profile in order to obtain high quality images. Through some image pre-processing with linear filtering, continuous contour searching method and circular detection based on random Hough transform (RHT), the real-time deformation can be measured with image characteristic parameters. In the practical application, the deformation of the loaded bicycle handle-bar is calculated. The test results show that the machine vision measurement is very effective; measurement resolution attains 0.1mm/pixel; the discrete degree of measurement data is low and the system meets the requirement of real-time measurement. The study proves that the measurement method of dynamic deformation based on machine vision is feasible, which can give some help for fatigue strength test of machine part and other structure deformation.


2015 ◽  
Vol 57 (5) ◽  
Author(s):  
Matthias Nießner

AbstractIn the last decade, computer-generated images have become a vital and integral part of our everyday lives. The quality of these images depends considerably on the geometric representation of the underlying virtual 3D environments. Subdivision surfaces, one such representation, have been found to be very useful due to their unique geometric properties. These properties led to the adaptation of subdivision surfaces as a movie industry standard for modeling 3D geometry, making subdivision surfaces indispensable in today's film productions. However, despite the high surface quality of subdivision surfaces, the complexity of underlying calculations requires a significant computational budget. In this thesis, we address this problem and propose novel algorithms to accelerate the evaluation of subdivision surfaces by several orders of magnitude. This enables the rendering of high-quality movie content on commercially available desktop computers within only a few milliseconds, opening up the possibility of using subdivision surfaces in real-time applications (e. g., video games). The results of this work have been made publicly available in Pixar's open source initiative


2018 ◽  
Vol 78 (2) ◽  
pp. 2251-2268
Author(s):  
Yanjun Peng ◽  
Qiaoling Li ◽  
Yingying Yan ◽  
Qiong Wang

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