Yet Another Appearance-Based Method for Pose Estimation Based on a linear Model
نویسندگان
چکیده
This paper explores the possibility of a linear model as a solution to the problem of appearance-based pose estimation. The parametric eigenspace method (or its extensions that are based on correlation between images) has been widely used and yields successful results for the pose estimation problem. On the other hand, the method has some problems. One is that large computational cost and storage space are required. Another is that small changes in appearance can be discarded even if it is related to changes of parameters to be estimated. Based on these, another appearance-based method for estimating pose of an object using a linear model is examined. Experimental results are not superior to the eigenspace method in terms of estimation accuracy. However, it has several advantages to the parametric eigenspace method in terms of storage space and computational cost, and has several features that can be advantages to the eigenspace method.
منابع مشابه
استفاده از برآورد حالتهای پویای دست مبتنی بر مدل، برای تقلید عملکرد بازوی انسان توسط ربات با دادههای کینکت
Pose estimation is a process to identify how a human body and/or individual limbs are configured in a given scene. Hand pose estimation is an important research topic which has a variety of applications in human-computer interaction (HCI) scenarios, such as gesture recognition, animation synthesis and robot control. However, capturing the hand motion is quite a challenging task due to its high ...
متن کاملGaze Estimation Using Active Appearance Model Parameters Based on Regression Analysis
One of the most crucial techniques associated with computer vision is technology that deals with the automatic estimation of gaze orientation. In this paper, a method is proposed to estimate horizontal gaze orientation from a monocular camera image using parameters of an Active Appearance Model (AAM) based on linear regression or non-linear regression. The proposed method can estimate horizonta...
متن کاملAccurate Interpolation in Appearance-Based Pose Estimation
One problem in appearance-based pose estimation is the need for many training examples, i.e. images of the object in a large number of known poses. Some invariance can be obtained by considering translations, rotations and scale changes in the image plane, but the remaining degrees of freedom are often handled simply by sampling the pose space densely enough. This work presents a method for acc...
متن کاملObject Pose Estimation by Locally Linearly Embedded Regression
In this paper we propose a new local learning algorithm for appearance-based object pose estimation, called Locally Linearly Embedded Regression (LLER). LLER uses a constrained version of Locally Linear Embedding (LLE) to simultaneously embed into an intermediate low-dimensional space the training images, the query image and a grid of pose parameters. A linear map is learned between the points ...
متن کاملYet another Method for Pose Estimation: A Probabilistic Approach using Points, Lines, and Cylinders
In this work, we use points, lines, and the linear extremal contours of cylinders to estimate the position and orientation of the camera in the world coordinate system. Other line-based pose estimation methods use the correspondences between 3D lines in space and 2D image lines, although the model and its observation are nite line segments. We present a noise model describing the probabilistic ...
متن کامل