We pose the problem of recognizing different types of human gait in the space of dynamical systems where each gait is represented. Established techniques are employed to track a k...
Alessandro Bissacco, Alessandro Chiuso, Yi Ma, Ste...
We present our work on using statistical, corpus-based machine learning techniques to simultaneously recognize an agent's current goal schemas at various levels of a hierarch...
Autoassociator is an important issue in concept learning, and the learned concept of a particular class can be used to distinguish the class from the others. For nonlinear autoass...
Recent work on unsupervised feature learning has shown that learning on polynomial expansions of input patches, such as on pair-wise products of pixel intensities, can improve the...
In this paper, we address the problems of deformable object matching (alignment) and segmentation with cluttered background. We propose a novel hierarchical log-linear model (HLLM...
Long Zhu, Yuanhao Chen, Xingyao Ye, Alan L. Yuille