TY - GEN
T1 - A convex decomposition methodology for collision detection
AU - Chowriappa, Ashirwad
AU - Wirz, Raul
AU - Ashammagari, Aditya R.
AU - Kesavadas, Thenkurussi
PY - 2013/10/7
Y1 - 2013/10/7
N2 - In this paper, a shape decomposition methodology to decompose the cervical spine using an approximate convex methodology is proposed. The proposed methodology identifies the most concave L-ring neighborhood in a decomposition of a surface (manifold-2) and partitions it in order to reduce its concavity. A close approximation of the original surface by a set of convex surfaces hulls is then produced.
AB - In this paper, a shape decomposition methodology to decompose the cervical spine using an approximate convex methodology is proposed. The proposed methodology identifies the most concave L-ring neighborhood in a decomposition of a surface (manifold-2) and partitions it in order to reduce its concavity. A close approximation of the original surface by a set of convex surfaces hulls is then produced.
KW - Cervical spine
KW - Convex decomposition
KW - Haptic
UR - http://www.scopus.com/inward/record.url?scp=84884863235&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84884863235&partnerID=8YFLogxK
U2 - 10.1109/VR.2013.6549361
DO - 10.1109/VR.2013.6549361
M3 - Conference contribution
AN - SCOPUS:84884863235
SN - 9781467347952
T3 - Proceedings - IEEE Virtual Reality
SP - 57
EP - 58
BT - IEEE Virtual Reality Conference 2013, VR 2013 - Proceedings
T2 - 20th IEEE Virtual Reality Conference, VR 2013
Y2 - 16 March 2013 through 20 March 2013
ER -