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 ...
The performance of face recognition systems that use two-dimensional images depends on factors such as lighting and subject's pose. We are developing a face recognition system...
In this paper we perform 3D face tracking on corrupted video sequences. We use a deformable model, combined with a predictive filter, to recover both the rigid transformations and...
Siome Goldenstein, Christian Vogler, Dimitris N. M...
The problem of pose estimation arises in many areas of computer vision, including object recognition, object tracking, site inspection and updating, and autonomous navigation when...
Philip David, Daniel DeMenthon, Ramani Duraiswami,...
This paper presents a new method for segmenting and recognizing Chinese handwritten address character strings. First, a dissection algorithm is applied to over-segment string imag...