My talk this week (Casey)

My talk has below parts:
1.The related work: Robust Real-time Object Detection.(Author: Viola & Jones)
2.Detection approach of HandVu System
3.Tracking Approach of HandVu System
4.Recognition

The information of this paper:

It is in IEEE Intl. Conference on Automatic Face and Gesture Recognition, May 2004.

Robust Hand Detection
Mathias K¨olsch and Matthew Turk
Department of Computer Science, University of California, Santa Barbara, CA

Abstract
Vision-based hand gesture interfaces require fast and extremely
robust hand detection. Here, we study view-specic
hand posture detection with an object recognition method
recently proposed by Viola and Jones. Training with this
method is computationally very expensive, prohibiting the
evaluation of many hand appearances for their suitability
to detection. As one contribution of this paper, we present a
frequency analysis-based method for instantaneous estimation
of class separability, without the need for any training.
We built detectors for the most promising candidates, their
receiver operating characteristics conrming the estimates.
Next, we found that classication accuracy increases with
a more expressive feature type. As a third contribution, we
show that further optimization of training parameters yields
additional detection rate improvements. In summary, we
present a systematic approach to building an extremely robust
hand appearance detector, providing an important step
towards easily deployable and reliable vision-based hand
gesture interfaces.

And Below is the autor's Ph.D thesis, "Vision Based Hand Gesture Interfaces for Wearable Computing and Virtual Environments"
You can download these two paper and get the author's information from this link: http://www.movesinstitute.org/~kolsch/publications.html