Model-based image recognition requires a general model of the object that should be detected in an image. In many applications such models are not known a-priori instead of they mu...
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Abstract— This paper proposes a method for learning viewpoint detection models for object categories that facilitate sequential object category recognition and viewpoint planning...
Abstract. In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class member...