Linear 3-D Object Pose Estimation with Dense Sample Images -Discussions about Limitation of Parameter Estimation Ability by the Linear Regressions-

In the image parameter estimation by the linear regression, it has very high degrees of freedom for the decision of regression coefficients, because the dimension of image vector is huge high. In this paper, we discuss its potential by the learning of the dense samples. For the learning process, we employed a sequential regression coefficient calculation algorithm and realize its calculation for dense samples with reasonable computational cost. Through the experimental result, we discuss about the limitation of parameter estimation ability by the linear regression.