Intuitive illustration of multiple Cayley-Klein metrics and single Cayley-Klein metric by a toy example.

<p>(a) non-linear metric VS. linear metrics. (b) multiple non-linear metrics VS. single non-linear metric.</p

Running times on OSR and PubFig.

<p>Running times on OSR and PubFig.</p

Illustrative experiment on Segmentation dataset in 2D.

<p>(a)∼(c) Distributions of training points under the learned metrics (MMC, CK-MMC and MCKML) respectively. (d)∼(f) Distributions of test points under the learned metrics (MMC, CK-MMC and MCKML) respectively.</p

Classification accuracies for each identity (mean in %) and average accuracies (mean and standard deviation in %) obtained on the PubFig dataset.

<p>Classification accuracies for each identity (mean in %) and average accuracies (mean and standard deviation in %) obtained on the PubFig dataset.</p

Characteristics and experiment settings of the UCI datasets.

<p>Characteristics and experiment settings of the UCI datasets.</p

Eight 3D lines (in pink color) on two orthogonal planes used in the simulations, where the small pyramids stand for camera viewpoints.

<p>Eight 3D lines (in pink color) on two orthogonal planes used in the simulations, where the small pyramids stand for camera viewpoints.</p

Distances between the edges on the unit cube by the three metrics.

<p>Distances between the edges on the unit cube by the three metrics.</p

Distances computed by the three metrics for P-I, P-II, O-I and O-II.

<p>Distances computed by the three metrics for P-I, P-II, O-I and O-II.</p

Experimental results.

<p>(a) Calibration cube; (b) planar checkerboard; (c) model house; (d) corridor.</p

Linear algorithm: LINa.

<p>Linear algorithm: LINa.</p