Computer Vision-Based Gesture Recognition for an Augmented Reality Interface (Storring, et al – 2004)

Current Mood: studious

Blogs I Commented On:

• Pankaj Rajan
• Aaron Wolin
• Brandon Paulson

Summary:
The gesture recognition system described in this paper is geared to supplement an augmented reality system, primarily for round-table meetings. The authors focus on six gestures of various outstretched fingers for their interface, requiring that users adapt to the hard limitation that these gestures be performed on a plane. Segmentation is done using a color pixel-based approach by segmenting blobs of similar color in the image. This approach uses normalized RGB to achieve invariance in order to transform the RGB colors to a color space that separates the intensity from the color space. In addition, skin blobs are defined with a minimum and maximum number of pixels. After segmenting hand pixels from the image, the hand and fingers are approximated as a circle and a number of rectangles for gesture recognition. The numbers of rectangles represent the number of outstretched fingers, which would involve doing a polar transformation around the center of the hand and counting the number of fingers present in each radius. To speed up the algorithm, they sample along concentric circles instead. Final classification is done by finding the number of fingers which is present for the most concentric circles. Recognized gestures are further filtered by a temporal filter, which means holding the gesture for a number of frames.

Discussion:
This paper takes a computer vision approach for gesture recognition, and what was nice about the paper was the technique of concentric circles in determining which and how many fingers were outstretched for particular gestures. It’s quite novel and reminiscent of the technique Oltmanns used in his dissertation. On the other hand, the authors required a hard limit to do so, and this takes away from the robustness of their system. Existing methods in computer vision could probably perform just as well with their hard limit, and yet still function better without it as well.