Yet Another Appearance-Based Method for Pose Estimation Based on a linear Model

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.

• Type: Conference
• Year: 2000
• Where: MVA
• Authors: Takayuki Okatani, Koichiro Deguchi
• Keywords: Eigenspace Method, MVA 2000, MVA 2007, Parametric Eigenspace Method, Pose Estimation