Vision Based Hand Gesture Interfaces for Wearable Computing and ...

Chapter 5. Hand Detection
corresponding detectors and state for every pixel the probability that it belonged
to the hand versus to background in the training data.
No grey-level fiducials or colored markers are employed and still a good de-
tection accuracy is achieved. This is possible due to the multi-cue integration
of texture and skin color. Other than in the tracking method explained in the
following chapter, both modalities must report a positive match for the detection
to be successful. This makes sense as a false positive is potentially more harmful
than a false negative, assuming that subsequent frames will eventually correctly
detect the initialization posture.
5.8 Hand pixel probability maps
The grey-level appearance-based hand detector finds rectangular areas that
contain hands. Not every pixel within those areas is likely to belong to a hand,
however, and some pixels will belong to the background. This spatial probability
distribution is defined for each posture and estimated from training images. Fig-
ure 5.16 shows the probability maps for six postures. A brighter pixel indicates
a higher probability that the respective pixel in the detected area is going to be
belong to the hand, that is, to be of skin color.
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