  In this paper, we proposed a pose estimation system based on rendered image
training set, which predicts the pose of objects in real image, with knowledge
of object category and tight bounding box. We developed a patch-based
multi-class classification algorithm, and an iterative approach to improve the
accuracy. We achieved state-of-the-art performance on pose estimation task.
