Hybrid generative-discriminative techniques and, in particular, generative score-space classification methods have proven to be valuable approaches in tackling difficult object or...
Alessandro Perina, Marco Cristani, Umberto Castell...
Finding the largest consensus set is one of the key ideas used by the original RANSAC for removing outliers in robust-estimation. However, because of its random and non-determinis...
In the context of variational image segmentation, we propose a new finite-dimensional implicit surface representation. The key idea is to span a subset of implicit functions with ...
Benoit Mory, Roberto Ardon, Anthony J. Yezzi, Jean...
Non-frontal view facial expression recognition is important in many scenarios where the frontal view face images may not be available. However, few work on this issue has been don...
Wenming Zheng, Hao Tang, Zhouchen Lin, Thomas S. H...
One important problem in computer vision is to provide a demographic description a person from an image. In practice, many of the state-of-the-art methods use only an analysis of ...
The varying object appearance and unlabeled data from new frames are always the challenging problem in object tracking. Recently machine learning methods are widely applied to tra...
We propose a multi-object multi-camera framework for tracking large numbers of tightly-spaced objects that rapidly move in three dimensions. We formulate the problem of finding co...
Zheng Wu, Nickolay I. Hristov, Tyson L. Hedrick, T...
A fundamental problem in computer vision (CV) is the estimation of geometric parameters from multiple observations obtained from images; examples of such problems range from ellip...
We present an integrated model for visual object localization and continuous state estimation in a discriminative structured prediction framework. While existing discriminative `p...
Measuring image similarity is a central topic in computer vision. In this paper, we learn similarity from Flickr groups and use it to organize photos. Two images are similar if th...