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The Mechanism And Characteristics Of Face Processing On University Students

Posted on:2020-08-21Degree:MasterType:Thesis
Country:ChinaCandidate:Z H MaoFull Text:PDF
GTID:2417330590481051Subject:Education
Abstract/Summary:PDF Full Text Request
Face information is loaded with a lot of information related to individuals.Through face recognition,we can effectively obtain important information such as the gender,age,ethnicity and emotional status of individuals.Therefore,this study mainly discuss the processing mechanism of face and object recognition of different ethnic groups.Experiment 1: the Chinese and uighurs as subjects,asked participants to classify the han Chinese and uighurs,face and object images of different rotation Angle(0 °,60 °,90 °,120 °,180 °).Experiments were conducted to explore the characteristics of the structure processing strategy in recognizing own race face,other race face and object images.The behavior results show that: in the object recognition,the classification of objects is significantly faster than faces,and the plane rotation does not affect the recognition of objects.In the face recognition,the subjects have certain advantages in own race face recognition under the positive condition.Plane rotation affect the face recognition performance.In addition,for the Chinese subjects,the plane rotation had a greater impact on the recognition performance of own race face,and the face inversion effect was more obvious.For Uygurs subjects,the effect of plane rotation on the faces of own race ethnic group and the faces of other ethnic groups was same,which was different from that of Chinese subjects.The ERP results show that: in the object recognition,there is no significant difference in amplitude of P100,N170 and LPP induced by upright face and planar rotation face.In the face recognition,faces showed greater amplitude than objects,while upside-down faces induced greater amplitude than upright faces.In the amplitudes of P100,N170 and LPP,we found that the amplitude induced by the plane rotating face was larger than that by the upright face,but the amplitude induced by the rotating face did not increase with the increase of rotation Angle.Experiment 2: the Chinese and Uighurs as subjects,the subjects were required to classify and judge the faces of Chinese nationality,Uighur nationality and object pictures which had damaged the local features.To explore the characteristics of feature processing strategy in recognizing own race face,other race face and object images.The behavior results show that the performance of object recognition is reduced when the local features are fuzzy.In the face recognition,the recognition performance of both own race faces and other race faces will decline after the local features are blurred.For the Chinese subjects,fuzziness had a greater impact on the recognition performance of the other race face.For Uygur subjects,the degree of influence of vagueness on the recognition of own race and other race face was consistent.The ERP results show that: only in LPP amplitude,we find that the LPP amplitude induced by face materials and object images was blurred and the amplitude show negative drift.To sum up,we have come up with the following conclusions:1.The structure processing and feature processing is also in the recognition process of the face,and the recognition of own race face show the structure processing advantage.The recognition of the other race face show the advantage of feature processing.2.The processing preferences of own race face and other race face will be affected by the contact experience to other race people.And the contact of other race people will make us that the processing of other race face is same own race.3.In the processing of face recognition,we first conduct the structure processing,and then the feature processing.Namely,the structure processing method occurs before the feature processing.4.In object recognition,more feature processing are used to process.And It is late than the processing of face.
Keywords/Search Tags:face recognition, own race effect, structure processing, feature processing, ERP
PDF Full Text Request
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