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This paper proposes an efficient way of modeling 3D faces by using only two - a frontal and a profile - images. Although it is desirable to utilize only one single image for 3D face modeling, more accurate depth information can be obtained if we use a profile face image additionally. Despite this seemly straightforward task, however, no standard solutions for 3D face modeling with two images have...
Three-dimensional face pose and shape acquisition has become an important part of 3D face reconstruction, 3D face tracking, and other related applications. Many approaches have been presented to estimate the 3D face shape from 2D images. Some of them are parameterized model based approaches so it is somewhat convenient to handle model shape and pose via numerical parameters to align its vertices on...
This paper presents a new method for person-specific face shape estimation under varying head pose of a previously unseen person from a single image. We describe a featureless approach based on a deformable 3D model and a learned face subspace. The proposed approach is based on maximizing a likelihood measure associated with a learned face subspace, which is carried out by a stochastic and genetic...
We present a stochastic filtering approach to perform albedo estimation from a single non-frontal face image. Albedo estimation has far reaching applications in various computer vision tasks like illumination-insensitive matching, shape recovery, etc. We extend the formulation proposed in that assumes face in known pose and present an algorithm that can perform albedo estimation from a single image...
This paper presents a new approach for the simultaneous estimation of the 3D pose and specific shape of a previously unseen face from a single image. The face pose is not limited to a frontal view. We describe a holistic approach based on a deformable 3D model and a learned statistical facial texture model. Rather than obtaining a person-specific facial surface, the goal of this work is to compute...
In this paper, we present some extensions to Active Appearance Model and its extended view-based models are applied for tracking faces through wide angles. The extensions include:(1) a new multiband representation created by filtering the images with a set of orthogonal spatial filters and then applying a non-linear normalization to them, and (2)adding extra landmarks outside the facial region to...
Three-dimensional face recognition has lately received much attention due to its robustness in the presence of lighting and pose variations. However, certain pose variations often result in missing facial data. This is common in realistic scenarios, such as uncontrolled environments and uncooperative subjects. Most previous 3D face recognition methods do not handle extensive missing data as they rely...
This paper addresses the recovering of 3D pose and animation of the human face in a monocular single image under uncontrolled imaging conditions. Our goal is to fit a 3D animated model in a face image with possibly large variations of head pose and facial expressions. Our data were acquired from filmed epileptic seizures of patients undergoing investigation in the videotelemetry unit, La Timone hospital,...
Face pose and illumination estimation is an important pre-processing step in many face analysis problems. In this paper, we present a new method to estimate the face pose and illumination direction from one single image. The basic idea is to compare the reconstruction residuals between the input image and a small set of reference images under different poses and illumination directions. Based on the...
This paper presents a real time, fully automatic facial feature detection and tracking approach. The head pose and facial action is tracked by a modified Candide 3D wireframe model based on an improved image registration technique. An effective model shape and position initialization method is also proposed. Experimental results demonstrate that our system is accurate, robust and fast enough for common...
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