Segmentation boundaries in accelerometer data of arm motion induced by music : online computation and perceptual assessment
Mendoza Garay, J. I. (2022). Segmentation boundaries in accelerometer data of arm motion induced by music : online computation and perceptual assessment. Human Technology, 18(3), 250-266. https://doi.org/10.14254/1795-6889.2022.18-3.4
Published inHuman Technology
©2022 Mendoza, and the Centre of Sociological Research, Poland
Segmentation is a cognitive process involved in the understanding of information perceived through the senses. Likewise, the automatic segmentation of data captured by sensors may be used for the identification of patterns. This study is concerned with the segmentation of dancing motion captured by accelerometry and its possible applications, such as pattern learning and recognition, or gestural control of devices. To that effect, an automatic segmentation system was formulated and tested. Two participants were asked to ‘dance with one arm’ while their motion was measured by an accelerometer. The performances were recorded on video, and manually segmented by six annotators later. The annotations were used to optimize the automatic segmentation system, maximizing a novel similarity score between computed and annotated segmentations. The computed segmentations with highest similarity to each annotation were then manually assessed by the annotators, resulting in Precision between 0.71 and 0.89, and Recall between 0.82 to 1. ...
PublisherCentre of Sociological Research
ISSN Search the Publication Forum1795-6889
Publication in research information system
MetadataShow full item record
Additional information about fundingThis study was partially funded by the Finnish Foundation for Technology Promotion (Tekniikan edistämissäätiö).
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