In this paper we address the problem of registering 3D scattered data by the mean of a statistical shape model. This model is built from a training set on which a principal compon...
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
This paper presents an algorithm for automatically detecting and segmenting a moving object from a monocular video. Detecting and segmenting a moving object from a video with limit...
Feng Liu (University of Wisconsin-Madison), Michae...
We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...