人眼检测的混合加权特征方法

Translated title of the contribution: Mixed Weighted Feature Method for Human Eye Detection

Jian Zhong Wang, Guang Yue Zhang, Hong Wang

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Eye gaze targeting technology based on eye movement tracking can free target tracking and aiming control of unmanned weapons from the need for limbs and make it possible to"attack whatever is seen", which is an important control mode of unmanned weapons in the future. A mixed weighted feature method was proposed in this paper. Human eye region detection was obtained through Gabor operator filtering, integral graph calculation, introducing local region variance as weight to weight mixed feature codes and combining it with cascade classifier training. The experimental results show that the method in this paper is better than the commonly used Haar-like and LDP methods, and the false detection rate shows a downtrend with the increase of series. This method can enhance the detection rate of human eyes and reduce false detection rate, providing a possible technical way to meet the requirements of real-time and accuracy of unmanned weapon eye gaze targeting.

Translated title of the contributionMixed Weighted Feature Method for Human Eye Detection
Original languageChinese (Traditional)
Pages (from-to)819-824
Number of pages6
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume39
Issue number8
DOIs
Publication statusPublished - 1 Aug 2019

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