This paper presents a framework for view-invariant action recognition in image sequences. Feature-based human detection becomes extremely challenging when the agent is being observ...
Bhaskar Chakraborty, Marco Pedersoli, Jordi Gonz&a...
This paper explores a recently proposed and rarely reported subspace learning method, Spectral Regression Discriminant Analysis (SRDA) [1, 2], on silhouette based human action rec...
We propose a new method ? Cubic Higher-order Local Auto-Correlation (CHLAC) ? to address three-way data analysis. This method is a natural extension of Higherorder Local Auto-Corr...
Applying learning techniques to acquire action models is an area of intense research interest. Most previous works in this area have assumed that there is a significant amount of...
We are developing a testbed for learning by demonstration combining spoken language and sensor data in a natural real-world environment. Microsoft Kinect RGBDepth cameras allow us...