Summary: CLASSIFICATION OF UNLABELED POINT SETS USING ANSIG
Jos´e J. Rodrigues, Jo~ao M. F. Xavier, Pedro M. Q. Aguiar
Institute for Systems and Robotics / IST, Lisboa, Portugal
We address two-dimensional shape-based classification, considering
shapes described by arbitrary sets of unlabeled points, or landmarks.
This is relevant in practice because, in many applications, the points
describing the shapes come from automatic processes, e.g., edge de-
tection, thus without labels. Rather than attempting to compute point
correspondences (a quagmire, when dealing with nontrivial shapes),
we use what we call the analytic signature (ANSIG) of the shapes,
a representation that has the key feature of being invariant to point
labeling. Geometric transformations, such as translation, rotation,
and scale, and different cardinality of point sets, are also dealt with
by this representation. We demonstrate the capabilities of our repre-
sentation with several shape classification experiments.
Index Terms-- Shape classification, shape representation, un-
labeled data, permutation invariance, analytic signature, ANSIG.