@Article{pirk:tg:2017,
  author    = {Pirk, S{\"o}ren and Krs, Vojtech and Hu, Kaimo and Rajasekaran, Suren Deepak and Kang, Hao and Benes, Bedrich and Yoshiyasu, Yusuke and Guibas, Leonidas J.},
  title     = {Understanding and Exploiting Object Interaction Landscapes},
  journal   = {ACM Transactions on Graphics},
  year      = {2017},
  volume    = {36},
  number    = {3},
  pages     = {1--14},
  month     = {June},
  doi       = {10.1145/3083725},
  url       = {https://storage.googleapis.com/pirk.io/papers/Pirk.etal-2017-InteractionLandscapes.pdf},
  abstract  = {Interactions play a key role in understanding objects and scenes, for
both virtual and real world agents. We introduce a new general representation
for proximal interactions among physical objects that is
agnostic to the type of objects or interaction involved. The representation
is based on tracking particles on one of the participating
objects and then observing them with sensors appropriately placed
in the interaction volume or on the interaction surfaces. We show
how to factorize these interaction descriptors and project them into
a particular participating object so as to obtain a new functional descriptor
for that object, its interaction landscape, capturing its observed
use in a spatio-temporal framework. Interaction landscapes
are independent of the particular interaction and capture subtle dynamic
effects in how objects move and behave when in functional
use. Our method relates objects based on their function, establishes
correspondences between shapes based on functional key points
and regions, and retrieves peer and partner objects with respect to
an interaction.},
  publisher = {ASSOC COMPUTING MACHINERY},
  address   = {2 PENN PLAZA, STE 701, NEW YORK, NY 10121-0701 USA}
}