Advanced Man-Machine Interaction: Fundamentals and by Karl-Friedrich Kraiss

By Karl-Friedrich Kraiss
Modern man-machine interfaces are more and more characterised by means of multimodality, nonintrusiveness, context-sensitivity, adaptivity, and teleoperability. The implementation of such houses is dependent upon novel options in felds equivalent to, e.g., machine imaginative and prescient, speech expertise, trainable classifiers, robotics, and digital fact. This publication places targeted emphasis on technological features of complicated interface implementation. moreover it specializes in interface layout and value. For readers with a heritage in engineering and desktop technological know-how, so much chapters provide layout directions and case stories, in addition to an outline of the functioning and obstacles of the algorithms required for implementation. additionally, complementary code examples in C++ are given the place acceptable. As a different function the ebook is observed by means of easy-to-handle software program improvement environments, which supply entry to huge public area software program for computing device imaginative and prescient, type, and digital fact. those environments additionally offer real-time entry to peripheral parts like, e.g., webcams or microphones, allowing hands-on experimentation and checking out.
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Extra info for Advanced Man-Machine Interaction: Fundamentals and Implementation (Signals and Communication Technology)
Example text
In other words, for any prior probabilities P (object), P (bg) = 0, all possible segmentations can be obtained by varying Θ from 0 to 1. g. 5. 3 This is usually easier to handle than the computation of exact values for P (object) and P (bg). 11) A suitable choice of Θ is crucial for an accurate discrimination between background and target. In case the recording conditions remain constant and are known in advance, Θ can be set manually, but for uncontrolled environments an automatic determination is desirable.
Texture features shall not be considered here because resolution and contrast that can be achieved with consumer cameras are usually insufficient for their reliable and accurate computation. 4. Recording conditions for the example recognition applications. 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.
Obviously, the test samples need to be sufficiently distinct from the training samples for this approach to be effective. 2 Classification Algorithms From the numerous strategies that exist for finding the best-matching class for an observation, three will be presented here: • • • A simple, easy-to-implement rule-based approach suitable for small vocabularies of static gestures. The concept of maximum likelihood classification, which can be applied to a multitude of problems. Hidden Markov Models (HMMs) for dynamic gestures.