Page 89 - Designing Sociable Robots

breazeal-79017 book March 18, 2002 14:2

70 Chapter 6

Figure 6.5
Sequence of foveal images with eye detection. The eye detector actually looks for the region between the eyes.
The box indicates a possible face has been detected (being both skin-toned and oval in shape). The small cross
locates the region between the eyes.

eye-detection system for Kismet (Breazeal et al., 2001). First, a set of feature filters are
applied successively to the image in increasing feature granularity. This serves to reduce the
computational overhead while maintaining a robust system. The successive filter stages are:

• Detect skin-colored patches in the image (abort if this does not pass above a threshold).
• Scan the image for ovals and characterize its skin tone for a potential face.
• Extract a sub-image of the oval and run a ratio template over it for candidate eye locations
(Sinha, 1994; Scassellati, 1998).
For each candidate eye location, run a pixel-based multi-layer perceptron (previously
•
trained) on the region to recognize shading characteristic of the eyes and the bridge of the
nose.

By doing so, the set of possible eye-locations in the image is reduced from the previous
level based on a feature filter. This allows the eye detector to run in real-time on a 400 MHz
PC. The methodology assumes that the lighting conditions allow the eyes to be distinguished
as dark regions surrounded by highlights of the temples and the bridge of the nose, that
human eyes are largely surrounded by regions of skin color, that the head is only moderately
rotated, that the eyes are reasonably horizontal, and that people are within interaction
distance from the robot (3 to 7 feet).