|Table of Contents|

Face detection based on improved speeded uprobust features algorithm(PDF)

《南京理工大学学报》（自然科学版）[ISSN:1005-9830/CN:32-1397/N]

Issue:
2017年06期
Page:
714-
Research Field:
Publishing date:

Info

Title:
Face detection based on improved speeded uprobust features algorithm
Author(s):
Hong Yang; Yu Fengqin
School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China
Keywords:
speeded up robust features;  face detection;  image entropy;  non-maximum suppression;  Haar wavelet response;  Fisher vector kernel
PACS:
TP391
DOI:
1005-9830(2017)06-0714-06
Abstract:
An improved speeded up robust features(SURF)algorithm is used in face detection aming at the shortcomings of many redundant information and low computing speed of the SURF algorithm.The image entropy of neighborhood of each feature point is calculated,and the feature points with high image entropy are selected by non-maximum suppression to decrease description area and redundant information.A fan window is used to traverse the neighborhood of each feature point,and Haar wavelet response in the fan window is calculated to form the descriptor of each feature point,and the computing speed is faster.Each descriptor is mapped into a high dimensional space by Fisher vector kernel for face detection.The simulation results in face detection data set and benchmark(FDDB)show that,compared with that of SURF algorithm,the detection rate of the improved SURF algorithm increases by 7.9%,the feature calculation time decreases by 53.1%,and the feature points decreases by 59.7%.

References:

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Last Update: 2017-12-31