Pose Normalisation for 3D Vehicles

Abstract

This study$^1$ investigates the various pose normalisation techniques that can be used for 3D vehicle models. A framework is built on which the pose normalisation performance of four PCA based techniques are tested on a database of 335 3D vehicles. The evaluation is performed using two methods. In the first method a silhouette view of each pose normalised vehicle is rendered from a consitent point in the 3D space. The pose consitency of each vehicle is then compared to the silhouettes of the vehicles in the same category. The second method compares the direct influence of the four techniques on the final precision and recall results of a search algorithm based on a simple scan-line feature descriptor. Results from both methods show that Center-of-Gravity PCA and Continous-PCA performed noticably better then PCA and Normal-PCA. The superiority of Continous-PCA over Center-of-Gravity PCA was negligible.

$^1$ This work is based on a report submitted in partial fulfilment of the BSc (Hons) Creative Computing in the University of London International Programmes