Gesture spotting with body-worn inertial sensors to detect user activities. Junker, H., Amft, O., Lukowicz, P., & Tröster, G. Pattern Recognition, 41(6):2010-2024, 6, 2008. Website abstract bibtex We present a method for spotting sporadically occurring gestures in a continuous data stream from body-worn inertial sensors. Our method is based on a natural partitioning of continuous sensor signals and uses a two-stage approach for the spotting task. In a first stage, signal sections likely to contain specific motion events are preselected using a simple similarity search. Those preselected sections are then further classified in a second stage, exploiting the recognition capabilities of hidden Markov models. Based on two case studies, we discuss implementation details of our approach and show that it is a feasible strategy for the spotting of various types of motion events.
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abstract = {We present a method for spotting sporadically occurring gestures in a continuous data stream from body-worn inertial sensors. Our method is based on a natural partitioning of continuous sensor signals and uses a two-stage approach for the spotting task. In a first stage, signal sections likely to contain specific motion events are preselected using a simple similarity search. Those preselected sections are then further classified in a second stage, exploiting the recognition capabilities of hidden Markov models. Based on two case studies, we discuss implementation details of our approach and show that it is a feasible strategy for the spotting of various types of motion events.},
bibtype = {article},
author = {Junker, Holger and Amft, Oliver and Lukowicz, Paul and Tröster, Gerhard},
journal = {Pattern Recognition},
number = {6}
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