Person-Independent Head Pose Estimation Using Biased Manifold Embedding
نویسندگان
چکیده
منابع مشابه
Person-Independent Head Pose Estimation Using Biased Manifold Embedding
Head pose estimation has been an integral problem in the study of face recognition systems and human-computer interfaces, as part of biometric applications. A fine estimate of the head pose angle is necessary and useful for several face analysis applications. To determine the head pose, face images with varying pose angles can be considered to be lying on a smooth low-dimensional manifold in hi...
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This paper describes an approach to head pose estimation in passport type images with an emphasis on high accuracy for near-frontal poses as well as person independence. Two different algorithms are proposed and compared. A Histogram of Oriented Gradients (HOG) descriptor is used for non-linear regression and a Biased Manifold Embedding (BME) approach is extended to cope with multiple poseangle...
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In this paper,wepropose a supervised SmoothMulti-Manifold Embedding (SMME) method for robust identity-independent head pose estimation. In order to handle the appearance variations caused by identity, we consider the pose data space as multiple manifolds in which each manifold characterizes the underlying subspace of subjects with similar appearance. We then propose a novel embedding criterion ...
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Recently, 3D object pose estimation is being focused. The Parametric Eigenspace method is known as one of the fundamental methods for this. It represents the appearance change of an object caused by pose change with a manifold embedded in a low-dimensional subspace. It obtains features by Principal Component Analysis (PCA), which maximizes the appearance variation. However, there is a problem t...
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ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2007
ISSN: 1687-6180
DOI: 10.1155/2008/283540