Tensor Decomposition and Non-linear Manifold Modeling for 3D Head Pose Estimation
نویسندگان
چکیده
منابع مشابه
Person Independent Head Pose Estimation by Non-Linear Regression and Manifold Embedding
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...
متن کاملHead Pose Estimation via Manifold Learning
For the last decades, manifold learning has shown its advantage of efficient non-linear dimensionality reduction in data analysis. Based on the assumption that informative and discriminative representation of the data lies on a low-dimensional smooth manifold which implicitly embedded in the original high-dimensional space, manifold learning aims to learn the low-dimensional representation foll...
متن کاملDeep Manifold Embedding for 3D Object Pose Estimation
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...
متن کاملHigher Order Support Tensor Regression for Head Pose Estimation
In this paper, we exploit the advantages of tensor representations and propose a Supervised Multilinear Learning Model for regression. The model is based on the Canonical (CANDECOMP)/Parallel Factors (PARAFAC) decomposition of tensors of multiple modes and allows the simultaneous projection of an input tensor to more than one discriminative directions along each mode. These projection weights a...
متن کاملPerson-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...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Vision
سال: 2019
ISSN: 0920-5691,1573-1405
DOI: 10.1007/s11263-019-01208-x