Towards artificial systems: What can we learn from human perception?

Heinrich H. Bülthoff, Lewis L. Chuang

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

Abstract

Research in learning algorithms and sensor hardware has led to rapid advances in artificial systems over the past decade. However, their performance continues to fall short of the efficiency and versatility of human behavior. In many ways, a deeper understanding of how human perceptual systems process and act upon physical sensory information can contribute to the development of better artificial systems. In the presented research, we highlight how the latest tools in computer vision, computer graphics, and virtual reality technology can be used to systematically understand the factors that determine how humans perform in realistic scenarios of complex task-solving.

Original languageEnglish
Title of host publicationPRICAI 2010
Subtitle of host publicationTrends in Artificial Intelligence - 11th Pacific Rim International Conference on Artificial Intelligence, Proceedings
Pages1-3
Number of pages3
DOIs
Publication statusPublished - 2010
Event11th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2010 - Daegu, Korea, Republic of
Duration: 2010 Aug 302010 Sep 2

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6230 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2010
CountryKorea, Republic of
CityDaegu
Period10/8/3010/9/2

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Bülthoff, H. H., & Chuang, L. L. (2010). Towards artificial systems: What can we learn from human perception? In PRICAI 2010: Trends in Artificial Intelligence - 11th Pacific Rim International Conference on Artificial Intelligence, Proceedings (pp. 1-3). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6230 LNAI). https://doi.org/10.1007/978-3-642-15246-7_1