Automatic Gender Classification through Face Segmentation
نویسندگان
چکیده
منابع مشابه
Automatic Face Representation and Classification
A working face recognition system requires the ability to represent facial images in such a way that permits efficient and accurate processing. The human visual system effectively stores, recognises and classifies familiar facial images under a wide variety of viewing conditions, albeit with various degrees of accuracy. We describe a system which automatically determines a representation for po...
متن کاملFace and Gender Classification in Crowd Video
Research in face and gender recognition under constrained environment has achieved an acceptable level of performance. There have been advancements in face and gender recognition in unconstrained environment, however, there is significant scope of improvement in surveillance domain. Face and gender recognition in such a setting poses a set of challenges including unreliable face detection, mult...
متن کاملReal-Time Gender Classification by Face
The identification of human beings based on their biometric body parts, such as face, fingerprint, gait, iris, and voice, plays an important role in electronic applications and has become a popular area of research in image processing. It is also one of the most successful applications of computer–human interaction and understanding. Out of all the abovementioned body parts,the face is one of m...
متن کاملAn Automatic Face Detection and Gender Classification from Color Images using Support Vector Machine
This paper presents combined face detection and gender classification method of discriminating between faces of men and women. This is done by detecting the human face area in image given and detecting facial features based on the measurements in pixels. The proposed algorithm converts the RGB image into the YCbCr color space to detect the skin regions from the facial image. But in order to det...
متن کاملAn Analysis of Automatic Gender Classification
Different researches suggest that inner facial features are not the only discriminative features for tasks such as person identification or gender classification. Indeed, they have shown an influence of features which are part of the local face context, such as hair, on these tasks. However, object-centered approaches which ignore local context dominate the research in computational vision base...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Symmetry
سال: 2019
ISSN: 2073-8994
DOI: 10.3390/sym11060770