Recently, the wide deployment of practical face recognition systems gives rise to the emergence of the inter-modality face recognition problem. In this problem, the face images in ...
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
We present a dynamic near-regular texture (NRT) tracking algorithm nested in a lattice-based Markov-Random-Field (MRF) model of a 3D spatiotemporal space. One basic observation use...
In this paper, we propose a two-level integrated model for accurate face shape alignment. At the low level, the shape is split into a set of line segments which serve as the nodes ...
Filtering based algorithms have become popular in tracking human body pose. Such algorithms can suffer the curse of dimensionality due to the high dimensionality of the pose state ...
Rui Li, Ming-Hsuan Yang, Stan Sclaroff, Tai-Peng T...
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
Visibility estimation is arguably the most difficult problem in dense 3D reconstruction from multiple arbitrary views. In this paper, we propose a simple new approach to estimating...
In order to analyze shapes of continuous curves in R3 , we parameterize them by arc-length and represent them as curves on a unit two-sphere. We identify the subset denoting the cl...
Abstract. We address the problem of comparing sets of images for object recognition, where the sets may represent arbitrary variations in an object's appearance due to changin...