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

Chapter 2. Literature Review
years. The interested reader is referred to two surveys by Yang, Kriegman, and
Ahuja [190] and Hjelm˚as and Low [60].
Little work has been done on finding hands in grey-level images based on their
appearance and texture. Wu and Huang [188] surveyed a number of methods for
their suitability to hand detection. Very recently, boosted classifiers have achieved
compelling results for view- and posture-independent hand detection as Ong and
Bowden demonstrated [124]. However, most of the hand detection methods resort
to less object-specific approaches and instead employ color information (see, for
example, Zhu et al. [196]), sometimes in combination with location priors (for ex-
ample, Kurata et al. [100]), motion flow (see Cutler and Turk [34]) or background
differencing (for example, Segen and Kumar [152]). The focus of the methods
developed for this dissertation is on reliable detection without placing severe con-
straints on the scenery. Those must use the maximum amount of information
available in the image, combining texture and color cues for reliability.
2.3.2 Tracking
If the detection method is fast enough to operate at image acquisition frame
rate, it can be used for tracking as well. However, tracking hands is notoriously
difficult since they can move very fast and their appearance can change vastly
within a few frames. On the other hand, mostly rigid objects can be tracked with
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