By Karl-Friedrich Kraiss
Modern man-machine interfaces are more and more characterised through multimodality, nonintrusiveness, context-sensitivity, adaptivity, and teleoperability. The implementation of such houses depends on novel options in felds equivalent to, e.g., laptop imaginative and prescient, speech expertise, trainable classifiers, robotics, and digital truth. This booklet places targeted emphasis on technological features of complex interface implementation. moreover it makes a speciality of interface layout and usefulness. For readers with a historical past in engineering and computing device technology, such a lot chapters provide layout directions and case experiences, in addition to an outline of the functioning and obstacles of the algorithms required for implementation. furthermore, complementary code examples in C++ are given the place applicable. As a unique function the e-book is observed by means of easy-to-handle software program improvement environments, which provide entry to huge public area software program for computing device imaginative and prescient, class, and digital truth. those environments additionally supply real-time entry to peripheral parts like, e.g., webcams or microphones, permitting hands-on experimentation and trying out.
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Additional info for Advanced Man-Machine Interaction: Fundamentals and Implementation (Signals and Communication Technology)
Concept This section introduces the basic concepts of HMMs on the basis of an example. In Fig. 16 the feature x˙ cog (t) has been plotted for three samples of the gesture “clockwise” (Fig. 3a). It is obvious that, while the three plots have similar shape, they are temporally displaced. We will ignore this for now and divide the time axis into segments of 5 observations each (one observation corresponds to one frame). 9 For each segment i, i = 1, 2, . . e. from 15 values each), as visualized in Fig.
Domain Condition(s) Image Content Ideally, the only skin colored object in the image is the user’s hand. Other skin colored objects may be visible, but they must be small compared to the hand. This also applies to the arm; it should be covered by a long-sleeved shirt if it is visible. In dynamic gestures the hand should have completely entered the image before recording starts, and not leave the image before recording ends, so that it is entirely visible in every recorded frame. Lighting Lighting is sufﬁciently diffuse so that no signiﬁcant shadows are visible on the hand.
This is provided if the selected features are approximately constant for multiple productions of the same gesture (low intra-gesture variance) but vary signiﬁcantly between different gestures (high inter-gesture variance). It is not required that different gestures differ in every element of the feature vector, but there must be at least one element in the feature vector that differs beyond the natural (unintentional) intra-gesture variance, segmentation inaccuracy, and noise. It is obvious that, in order to determine intra- and inter-gesture variance, a feature has to be computed for numerous productions of every gesture in the vocabulary.