ICA-based probabilistic local appearance models

X. S. Zhou, B. Moghaddam, T. S. Huang

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper proposes a novel image modeling scheme for object detection and localization. Object appearance is modeled by the joint distribution of k-tuple salient point feature vectors which are factorized component-wise after an independent component analysis (ICA). Also, we propose a distance-sensitive histograming technique for capturing spatial dependencies. The advantages over existing techniques include the ability to model non-rigid objects (at the expense of modeling accuracy) and the flexibility in modeling spatial relationships. Experiments show that ICA does improve modeling accuracy and detection performance. Experiments in object detection in cluttered scenes have demonstrated promising results.

Original languageEnglish (US)
Pages161-164
Number of pages4
StatePublished - 2001
EventIEEE International Conference on Image Processing (ICIP) 2001 - Thessaloniki, Greece
Duration: Oct 7 2001Oct 10 2001

Other

OtherIEEE International Conference on Image Processing (ICIP) 2001
Country/TerritoryGreece
CityThessaloniki
Period10/7/0110/10/01

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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