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Hardware Accelerated Image Processing on an FPGA-SoC Based Vision System for Closed Loop Monitoring and Additive Manufacturing Process Control Read chapter Read first chapter

2019 | OriginalPaper | Chapter

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

Authors : Costas Panagiotakis, Antonis Argyros

Published in: Computer Vision Systems

Publisher: 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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previous chapter Planar Pose Estimation Using Object Detection and Reinforcement Learning
next chapter Deep Residual Temporal Convolutional Networks for Skeleton-Based Human Action Recognition
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Metadata
Title
A Two-Stage Approach for Commonality-Based Temporal Localization of Periodic Motions
Authors
Costas Panagiotakis
Antonis Argyros
Copyright Year
2019
Book
Computer Vision Systems

Print ISBN: 978-3-030-34994-3

Electronic ISBN: 978-3-030-34995-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-34995-0_33

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