Synthesis of visible spectrum faces from thermal facial imagery is a promising approach for heterogeneous face recognition; enabling existing face recognition software trained on visible imagery to be leveraged, and allowing human analysts to verify cross-spectrum matches more effectively. We propose a new synthesis method to enhance the discriminative quality of synthesized visible face imager...

Face recognition, holistic processing, and processing of configural and featural facial information are known to be influenced by face race, with better performance for own- than other-race faces. However, whether these various other-race effects (OREs) arise from the same underlying mechanisms or from different processes remains unclear. The present study addressed this question by measuring t...

Approaches for cross-pose face recognition can be categorized into 2D image based and 3D model based. However, only a small number of 3D model based approaches are reported although 3D information is considered crucial for cross-pose analysis. Extended from a latest face reconstruction method using a single 3D reference model, this study focuses on using the reconstructed 3D face for recognitio...

Recently, fast neural networks for object/face detection were presented in [1-3]. The speed up factor of these networks based on cross correlation in the frequency domain between the input image and the weights of the hidden layer. But, these equations given in [1-3] for conventional and fast neural networks are not valid for many reasons presented here. In this paper, correct equations for cr...

1 Abstract Ample evidence suggests that face processing in human and non-human primates is performed differently compared with other objects. Converging reports, both physiologically and psychophysically, indicate that faces are processed in specialized neural networks in the brain – i.e. face patches in monkeys and the fusiform face area (FFA) in humans. We are all expert face-processing agent...