I have two studies on Silver Alerts where one study had a senior lady as the target and the other a senior male was the target.
These were separate studies.
Recognition of the Female face was low, 44%.
Recognition of the Male face was high 83.4%
I cannot find anything in the literature on why an older Male's face would have a higher recognition rate than an older Female face.
If Anyone knows of a study that shows in general, college age students (19 years of age) would recognize a male over a female face. I am puzzled. There were no age, gender, or race effects as well.
Vicki Gier
Yes, I had students rate attractiveness and for both the male and female in the different studies they were rated average, which is what I was shooting for.
The reduction wasn't between the Two Missing Male studies, it was comparing the Female to the Male Silver Alert. Students recognized the Male better than the female, but not gender or race effects.
Dear Vicki Gier
its very interesting study what you have done.Your done all the study in ideal condition or else , I have some doubts
1. All the face recognition done in one day??
2. They have any kind of make??
3. And something that have change their emotions??
Not sure if this will help but... I wonder if this is an issue of ambiance (along Anna Bobak's line of thinking)? When we have run experiments using faces and voices we have used multiple examples of stimuli in part to allow for random variation in the stimuli. Typically we have the run multilevel models with participants, stimuli (face) and stimuli voice as levels of the analysis. One finding we had (where participants were, matching voices to faces or faces to voices) and published, showed that some faces and voices are easier to put together than others i.e. some people have faces and voice that go together and others that don't. The point is that variation in stimuli (even stimuli that are of equal attractiveness) is an important aspect of natural face/voice processing. Just a difference in the camera used can affect how well a face is matched or remembered (e.g. Face A - camera 1 matching with Face A camera 1 is better than Face A - camera 1 matching with Face A camera 2). Mike Burton (York), Sally Andrews (NTU), Kay Ritchie (Lincoln), Mila Mileva (York), Robin Kramer (Lincoln), Rob Jenkins (York) have all worked on the problem of ambience in face stimuli (it's almost certainly true for voices too). Distinctivness is also an issue.
Hii...Yes, in my contribution I'm propsed a system for race recognition in which I found the accuracy of Asian 100 % is higher than Non-Assian 99,98 % ...but I didn't test the gender recognition...if you need a help contact me....My best regards
Refer Gender face recognition techniques you will get better idea about this:
1. Gender Face recognition using Deep Learning
https://www.sciencedirect.com/science/article/pii/S1877050918307853
2. Gender Face recognition from faces using deep learning
https://ieeexplore.ieee.org/document/8090181
3. Feature extraction based Face Recognition Gender and Age Classification
Article Feature Extraction based Face Recognition, Gender and Age Cl...
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