Publication details

Motion Words: A Text-like Representation of 3D Skeleton Sequences

Authors

SEDMIDUBSKÝ Jan BUDÍKOVÁ Petra DOHNAL Vlastislav ZEZULA Pavel

Year of publication 2020
Type Article in Proceedings
Conference 42nd European Conference on Information Retrieval (ECIR)
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1007/978-3-030-45439-5_35
Keywords 3D skeleton sequence;motion word;motion vocabulary;quantization;border problem;text-based processing
Description There is a growing amount of human motion data captured as a continuous 3D skeleton sequence without any information about its semantic partitioning. To make such unsegmented and unlabeled data efficiently accessible, we propose to transform them into a text-like representation and employ well-known text retrieval models. Specifically, we partition each motion synthetically into a sequence of short segments and quantize the segments into motion words, i.e. compact features with similar characteristics as words in text documents. We introduce several quantization techniques for building motion-word vocabularies and propose application-independent criteria for assessing the vocabulary quality. We verify these criteria on two real-life application scenarios.
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