Exploiting effective facial patches for robust gender recognition
نویسندگان
چکیده
منابع مشابه
Robust gender recognition by exploiting facial attributes dependencies
Estimating human face gender from images is a problem that has been extensively studied because of its relevant applications. Recent works report significant drops in performance for state-of-the-art gender classifiers when evaluated “in the wild,” i.e. with uncontrolled demography and environmental conditions. We hypothesize that this is caused by the existence of dependencies among facial dem...
متن کاملFacial expression recognition using salient facial patches
This paper proposes a novel facial expression recognition method composed of two main steps: offline step and online step. The offline step selects the most salient facial patches using mutual information technique. The online step relies on the already selected patches to identify the facial expression using an SVM classifier. In both steps, the LBP operator was used to extract facial expressi...
متن کاملRobust Facial Expression Recognition
This paper proposes a novel local feature descriptor, Local Directional Number Pattern (LDN), for face analysis: face and expression recognition. LDN encodes the directional information of the face’s textures (i.e., the texture’s structure) in a compact way, producing a more discriminative code than current methods. We compute the structure of each micro-pattern with the aid of a compass mask, ...
متن کاملDeep Colorization for Facial Gender Recognition
Recent research suggests that colorization models have the capability of generating plausible color versions from grayscale images. In this paper, we investigate whether colorization prior to gender classification improves classification performance on the FERET grayscale face dataset. For this, we colorize the images using an existing Lab colorization model, both with and without class rebalan...
متن کاملExploiting Competition Relationship for Robust Visual Recognition
Joint learning of similar tasks has been a popular trend in visual recognition and proven to be beneficial. Between-task similarity often provides useful cues, such as feature sharing, for learning visual classifiers. By contrast, the competition relationship between visual recognition tasks (e.g., content independent writer identification and handwriting recognition) remains largely under-expl...
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: Tsinghua Science and Technology
سال: 2019
ISSN: 1007-0214
DOI: 10.26599/tst.2018.9010090