View-based dynamic object recognition based on human perception

Heinrich Bulthoff, Christian Wallraven, Arnulf Graf

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


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
Pages (from-to)768-776
Number of pages9
JournalProceedings - International Conference on Pattern Recognition
Issue number3
Publication statusPublished - 2002

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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