ECHO: Extended Convolution Histogram of Orientations for Local Surface Description

Thomas W. Mitchel, Szymon Rusinkiewicz, Gregory S. Chirikjian, Michael Kazhdan

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a novel, highly distinctive and robust local surface feature descriptor. Our descriptor is predicated on a simple observation: instead of describing the points in the vicinity of a feature point relative to a reference frame at the feature point, all points in the region describe the feature point relative to their own frames. Isometry invariance is a byproduct of this construction. Our descriptor is derived relative to the extended convolution – a generalization of the standard convolution that allows the filter to adaptively transform as it passes over the domain. As such, we name our descriptor the Extended Convolution Histogram of Orientations (ECHO). It exhibits superior performance compared to popular surface descriptors in both feature matching and shape correspondence experiments. In particular, the ECHO descriptor is highly stable under near-isometric deformations and remains distinctive under significant levels of noise, tessellation, complex deformations and the kinds of interference commonly found in real data.

Original languageEnglish (US)
Pages (from-to)180-194
Number of pages15
JournalComputer Graphics Forum
Volume40
Issue number1
DOIs
StatePublished - Feb 2021

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design

Keywords

  • 3D shape matching
  • computer vision – shape recognition
  • curves and surfaces
  • methods and applications
  • modeling
  • modeling

Fingerprint

Dive into the research topics of 'ECHO: Extended Convolution Histogram of Orientations for Local Surface Description'. Together they form a unique fingerprint.

Cite this