FacebookTwitterGoogle PlusRSS News Feed

VASC Seminar: Talk Two

Visiting Scholar
Robotics Institute
Carnegie Mellon University
Facial Action Unit Event Detection by Cascade of Tasks
Monday, November 18, 2013 - 3:30pm to 4:00pm
Newell-Simon Hall

Automatic facial Action Unit (AU) detection from video is a long-standing problem in facial expression analysis. AU detection is typically posed as a classification problem between frames or segments of positive examples and negative ones, where existing work emphasizes the use of different features or classifiers. In this paper, we propose a method called Cascade of Tasks (CoT) that combines the use of different tasks (i.e., frame, segment and transition) for AU event detection. We train CoT in a sequential manner embracing diversity, which ensures robustness and generalization to unseen data. In addition to conventional framebased metrics that evaluate frames independently, we propose a new event-based metric to evaluate detection performance at event-level. We show how the CoT method consistently outperforms state-of-the-art approaches in both frame-based and event-based metrics, across three public datasets that differ in complexity: CK+, FERA and RU-FACS.


Xiaoyu Ding is a visiting scholar in Robotics Institute, Carnegie Mellon University. He works with Fernando De la Torre and Jeffrey F. Cohn. His research interests include practical aspects of computer vision and machine learning. In particular, he is working on facial expression analysis in videos.

Host: Kris Kitani

For More Information, Please Contact:

kkitani [atsymbol] cs ~replace-with-a-dot~ cmu ~replace-with-a-dot~ edu