View-based dynamic object recognition based on human perception

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)

Abstract

Psychophysical studies have shown that humans actively exploit temporal information such as contiguity of images in object recognition. We have recently developed a recognition system which uses temporal contiguity to learn extensible representations of objects on-line. The system performs well both on real-world and synthetic data and shows robustness under illumination changes. In this paper, we present results which compare the proposed representation against simple image-based representations of the same complexity using Minkowski Minimum Distance classifiers and Support Vector Machine classifiers. Recognition results for all classifiers show large improvements with incorporated temporal information.

Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
Pages768-776
Number of pages9
Volume16
Edition3
Publication statusPublished - 2002
Externally publishedYes

ASJC Scopus subject areas

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

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  • Cite this

    Bulthoff, H., Wallraven, C., & Graf, A. (2002). View-based dynamic object recognition based on human perception. In Proceedings - International Conference on Pattern Recognition (3 ed., Vol. 16, pp. 768-776)