TY - JOUR
T1 - An automatic balancing scheme for multi-articulated virtual objects
AU - Baek, Nakhoon
AU - Yoo, Kwan Hee
PY - 2013
Y1 - 2013
N2 - In many fields of computer science and other engineering areas, we often need to balance multi-articulated structures. In this paper, we formalize this kind of balancing problem from a more physical and theoretical point of view. Through describing details of all the solution steps, we finally represent a set of algorithms to automatically balance multi-articulated objects with tree topologies. Given the geometric configurations and masses at the leaf nodes of target multi-articulated objects, our algorithms achieve their balanced state through adjusting the mass of each node. To minimize the mass changes from the initial configuration, we use constraints of minimizing the norms of the mass differences between the initial masses and the final balanced masses. Actually, we use three different metrics, l1, l2 and l∞ norms. These norms show slightly different behaviors in the minimization process, and users can select one of them according to their preferences and application purposes. We show all the details of algorithms, their time complexity analyses, and experimental results.
AB - In many fields of computer science and other engineering areas, we often need to balance multi-articulated structures. In this paper, we formalize this kind of balancing problem from a more physical and theoretical point of view. Through describing details of all the solution steps, we finally represent a set of algorithms to automatically balance multi-articulated objects with tree topologies. Given the geometric configurations and masses at the leaf nodes of target multi-articulated objects, our algorithms achieve their balanced state through adjusting the mass of each node. To minimize the mass changes from the initial configuration, we use constraints of minimizing the norms of the mass differences between the initial masses and the final balanced masses. Actually, we use three different metrics, l1, l2 and l∞ norms. These norms show slightly different behaviors in the minimization process, and users can select one of them according to their preferences and application purposes. We show all the details of algorithms, their time complexity analyses, and experimental results.
KW - Balancing
KW - Minimization
KW - Tree-topology
UR - http://www.scopus.com/inward/record.url?scp=84873247811&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84873247811
SN - 1975-0080
VL - 8
SP - 139
EP - 150
JO - International Journal of Multimedia and Ubiquitous Engineering
JF - International Journal of Multimedia and Ubiquitous Engineering
IS - 1
ER -