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Gender Classification Based on Multi-Scale and Run-Length Features
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作者 Sheng-Hung Wang Chih-Yang Lin Jing-Tong Fu 《Journal of Electronic Science and Technology》 CAS CSCD 2017年第3期251-257,共7页
Human faces can convey substantial information about a person,such as his or her age,race,identity,gender,and emotions.Such facial information can be obtained through techniques like human facial tracking and detectio... Human faces can convey substantial information about a person,such as his or her age,race,identity,gender,and emotions.Such facial information can be obtained through techniques like human facial tracking and detection,facial recognition,gender classification,emotion recognition,as well as age estimation.Of these,gender classification is particularly important due to its diverse applications in the fields such as video surveillance and commercial advertising.In this thesis,we propose a method of gender classification based on run-length histograms.The proposed method uses a run-length histogram to record the position information of pixels,thereby efficiently improves the recognition rate and makes the technique suitable for a big-data multimedia database.The experimental results show that the proposed method can achieve better accuracy than a multi-scale based method can. 展开更多
关键词 Index terms--gender classification run-length texture feature.
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