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The key challenge of face recognition is to develop effective feature representations for reducing intra-personal variations while enlarging inter-personal differences. This paper presents a novel non-linear discriminant error criterion which can be used in effective feature learning from raw pixels. Unlike many existing methods which assume the problem to be linear in nature, the proposed method...
Recent advancement in unsupervised and transfer learning methods of deep learning networks has seen a complete paradigm shift in machine learning. Inspired by the recent evolution of deep learning (DL) networks that demonstrates a proven pathway of addressing challenging dilemmas in various problem domains, we propose a novel DL framework for expression-robust feature acquisition. The framework exploits...
In this paper, face recognition against mouth shape variations is investigated. In order to detect possible mouth variations, the inner mouth landmarks are first detected by a landmark detector and then used to estimate the connectivity between the upper lip and the lower lip of a face image. The vertical distance between the middle inner points of upper lip and the lower lip is calculated, and then...
In this paper we address the challenge of performing face recognition on human faces that are wearing glasses. This is a common problem for face recognition and automatic identity checking at airports, as passengers frequently forget to remove their glasses when passing through customs. In order to solve this problem, we first propose an automatic glasses presence detection model based on the tree-pictorial-structured...
This paper addresses the problem of person-independent 4D facial expression recognition. Unlike the majority of existing works, we propose to extract spatio-temporal features in 4D data (3D expression sequences changing over time) to represent 3D facial expression dynamics sufficiently, rather than extracting features frame-by-frame. First, the proposed method extracts local depth patch-sequences...
Facial expressions form a significant part of our nonverbal communications and understanding them is essential for effective human computer interaction. Due to the diversity of facial geometry and expressions, automatic expression recognition is a challenging task. This paper deals with the problem of person-independent facial expression recognition from a single 3D scan. We consider only the 3D shape...
High-resolution functional magnetic resonance imaging (hi-res fMRI) methodology offers an opportunity for neuroscientists to gain insight about brain activities at a finer scale, and is thus becoming increasingly common. Traditional voxel-wise general linear model (GLM) is not suitable for hi-res functional brain mapping because local averaging may lose valuable fine-grained information boasted by...
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