TY - GEN
T1 - Haptic rendering of point set surfaces
AU - Lee, Jae Kyu
AU - Kim, Young J.
PY - 2007
Y1 - 2007
N2 - We present a haptic rendering algorithm for a point set surface. Given a point set, its point set surface is an implicit surface defined by local projection of point sets using the moving least square (MLS) method. Our haptic algorithm is a penalty-based method which requires a calculation of the minimum distance between the haptic interaction point (HIP) and point set surfaces. Thus, a rapid calculation of this distance is the main ingredient of our haptic rendering algorithm. As preprocess, our algorithm builds a bounding volume hierarchy (BVH) of swept sphere volumes (SSV) for each of given point sets. Here, the SSV is defined as volume swept by a moving sphere. Then, at run-time, we find apair of closest points between the point set and HIP using a SSV hierarchy. We attempt to further refine the distance by projecting the closest pair of point to its local point set surface by using the MLS projection. In order to execute the MLS projection, we need to find points in a local neighborhood of the closest point pair. We again use the SSV hierarchy to find the neighborhood by performing collision detection between a sphere, defining the local neighborhood, and the SSV hierarchy. This results in a highly fast and reliable calculation of closest surface distance between the point set model and HIP. In practice, our algorithm takes 0.2 - 0.3 msec to calculate haptic feedback for a point set consisting of more than 24K points.
AB - We present a haptic rendering algorithm for a point set surface. Given a point set, its point set surface is an implicit surface defined by local projection of point sets using the moving least square (MLS) method. Our haptic algorithm is a penalty-based method which requires a calculation of the minimum distance between the haptic interaction point (HIP) and point set surfaces. Thus, a rapid calculation of this distance is the main ingredient of our haptic rendering algorithm. As preprocess, our algorithm builds a bounding volume hierarchy (BVH) of swept sphere volumes (SSV) for each of given point sets. Here, the SSV is defined as volume swept by a moving sphere. Then, at run-time, we find apair of closest points between the point set and HIP using a SSV hierarchy. We attempt to further refine the distance by projecting the closest pair of point to its local point set surface by using the MLS projection. In order to execute the MLS projection, we need to find points in a local neighborhood of the closest point pair. We again use the SSV hierarchy to find the neighborhood by performing collision detection between a sphere, defining the local neighborhood, and the SSV hierarchy. This results in a highly fast and reliable calculation of closest surface distance between the point set model and HIP. In practice, our algorithm takes 0.2 - 0.3 msec to calculate haptic feedback for a point set consisting of more than 24K points.
UR - http://www.scopus.com/inward/record.url?scp=34548133626&partnerID=8YFLogxK
U2 - 10.1109/WHC.2007.67
DO - 10.1109/WHC.2007.67
M3 - Conference contribution
AN - SCOPUS:34548133626
SN - 0769527388
SN - 9780769527383
T3 - Proceedings - Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, World Haptics 2007
SP - 513
EP - 518
BT - Proceedings - Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, World Haptics 2007
T2 - 2nd Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, World Haptics 2007, WHC'07
Y2 - 22 March 2007 through 24 March 2007
ER -