First Year PhD Report Extracting Motion Primitives from Natural Handwriting Data
نویسنده
چکیده
Movement selection and control is a very difficult inverse dynamics problem for robotic control that humans and animals accomplish easily. For the past 10 years there has been a popular theory that biological movement is made up of sub-routine type blocks, or ‘motor primitives’, with a central controller timing the activation of these blocks, creating synergies of muscle activation. Using machine learning techniques, this project addresses the possibility of extracting useful, and repeatable motor primitives from handwriting data.
منابع مشابه
Second Year PhD Report Extracting Motion Primitives from Natural Handwriting Data
Biological movement control and planning is based upon motor primitives. Each motor primitive takes responsibility for controlling a small sub-block of motion, containing coherent muscle activation outputs. A central timing controller cues these subroutines of movement, creating complete movement strategies that are built up by overlaying primitives, thus creating synergies of muscle activation...
متن کاملExtracting Motion Primitives from Natural Handwriting Data
For the past 10 years it has become clear that biological movement is made up of sub-routine type blocks, or motor primitives, with a central controller timing the activation of these blocks, creating synergies of muscle activation. This paper shows that it is possible to use a factorial hidden Markov model to infer primitives in handwriting data. These primitives are not predefined in terms of...
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Biological movement is built up of sub-blocks or motion primitives. Such primitives provide a compact representation of movement which is also desirable in robotic control applications. We analyse handwriting data to gain a better understanding of primitives and their timings in biological movements. Inference of the shape and the timing of primitives can be done using a factorial HMM based mod...
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Biological movement control and planning is based upon motor primitives. In our approach, we presume that each motor primitive takes responsibility for controlling a small sub-block of motion, containing coherent muscle activation outputs. A central timing controller cues these subroutines of movement, creating complete movement strategies that are built up by overlaying primitives, thus creati...
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The aim of my PhD research is focused on Text Mining (TM), one major school in Knowledge Discovery in Data (KDD), and in particular the classification / categorization of documents utilizing novel algorithms for the identification of hidden patterns, rules, regularities and trends within these documents. Two significant techniques of Data Mining (DM), another well-known KDD school, are involved...
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