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2019 | OriginalPaper | Buchkapitel

A Two-Stage Approach for Commonality-Based Temporal Localization of Periodic Motions

verfasst von : Costas Panagiotakis, Antonis Argyros

Erschienen in: Computer Vision Systems

Verlag: Springer International Publishing

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Abstract

We present an unsupervised method for the detection of all temporal segments of videos or motion capture data, that correspond to periodic motions. The proposed method is based on the detection of similar segments (commonalities) in different parts of the input sequence and employs a two-stage approach that operates on the matrix of pairwise distances of all input frames. The quantitative evaluation of the proposed method on three standard ground-truth-annotated datasets (two video datasets, one 3D human motion capture dataset) demonstrate its improved performance in comparison to existing approaches.

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Metadaten
Titel
A Two-Stage Approach for Commonality-Based Temporal Localization of Periodic Motions
verfasst von
Costas Panagiotakis
Antonis Argyros
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-34995-0_33

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