Human face detection with neural networks and the DIRECT algorithm

Yau Zen Chang*, Kao Ting Hung, Shih Tseng Lee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Based on Rowley's approach [2], this paper aims at proposing a new architecture that uses a specific optimization technique, the DIRECT (DIviding RECTangle) algorithm, to improve the efficiency of face detection in images. The system consists of two main parts: a neural network-based face detection arbitrator and a search strategy based on an integer-handling DIRECT algorithm. By the architecture, the number of arbitration is dramatically reduced, and human faces, if they are present in an image, are not restricted to predetermined resolutions and aspect ratios. Experimental results show that the proposed architecture is efficient in terms of both speed and robustness.

Original languageEnglish
Title of host publicationProceedings of the 12th International Symposium on Artificial Life and Robotics, AROB 12th'07
Pages60-63
Number of pages4
StatePublished - 2007
Event12th International Symposium on Artificial Life and Robotics, AROB 12th'07 - Oita, Japan
Duration: 25 01 200727 01 2007

Publication series

NameProceedings of the 12th International Symposium on Artificial Life and Robotis, AROB 12th'07

Conference

Conference12th International Symposium on Artificial Life and Robotics, AROB 12th'07
Country/TerritoryJapan
CityOita
Period25/01/0727/01/07

Keywords

  • DIRECT algorithm
  • Face detection
  • Image pattern recognition
  • Image processing
  • Neural network

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