INTRODUCTION Difficulty recognizing emotions may contribute to childhood anxiety and anxiety-related social difficulties. METHODS We examined the relationship between gender and emotion recognition accuracy in children with and without anxiety disorders. RESULTS Gender did not predict emotion recognition accuracy except for disgust. DISCUSSION Disgust recognition was significantly less ac...

Faces are notoriously hard to perceive when turned upside-down. It is often claimed that perceptual decrements reflect a qualitative switch from parallel whole-face processing, to a serial analysis of individual features. To test this view, we examined observers' ability to categorize faces presented in their entirety, or viewed through a dynamic aperture that moved incrementally across the fac...

Prior research has demonstrated that feminine appearance is penalized in business contexts. However, a separate body of research, predominantly centered on electoral outcomes, has put forth conflicting results demonstrating that feminine appearance can be beneficial. In a series of experimental studies, I aim to resolve the conflict in the literature by proposing an expectationmatching theory. ...

Gender recognition plays an important role for a wide range of application in the field of Human Computer Interaction. In this paper, we propose a gender recognition system based on 2D Discrete Cosine Transform and Neural Networks. In particular, a discriminability criterion is used to select the DCT coefficients that make up the biometric template. Experimental results show how the proposed ap...

Gender Recognition in Face Recognition System has prevalent applications in the fields of demographic data collection, video surveillance, security, retail advertising and marketing and it also plays a vital role on object recognition in robot research area, which has shown an intensive attention in the past few years.However, face recognition is still a challenging task since face images are e...

Computer vision-based gender classification is an interesting and challenging problem, and has potential applications in visual surveillance and human–computer interaction systems. In this paper, we investigate gender classification from human gaits in image sequences, a relatively understudied problem. Moreover, we propose to fuse gait and face for improved gender discrimination. We exploit ca...

Recognition memory accuracy is harmed by prior testing (a.k.a., output interference [OI]; Tulving & Arbuckle, 1966). In several experiments, we interpolated various tasks between recognition test trials. The stimuli and the tasks were more similar (lexical decision [LD] of words and nonwords) or less similar (gender identification of male and female faces) to the stimuli and task used in recogn...

The current event-related fMRI study examined the relative involvement of different parts of the medial temporal lobe (MTL), particularly the contribution of hippocampus and perirhinal cortex, in either intentional or incidental recognition of famous faces in contrast to unfamiliar faces. Our intention was to further explore the controversial contribution of MTL in the processing of semantic me...

The human hand possesses distinctive features which can reveal gender information. In addition, the hand is considered one of the primary biometric traits used to identify a person. In this work, we propose a large dataset of human hand images with detailed ground-truth information for gender recognition and biometric identification. The proposed dataset comprises of 11,076 hand images (dorsal ...

Gender information has many useful applications in computer vision systems, such as surveillance systems, counting the number of males and females in a shopping mall, accessing control systems in restricted areas, or any human-computer interaction system. In most previous studies, researchers attempted to recognize gender by using visible light images of the human face or body. However, shadow,...