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Dynamic Time Warping (DTW) is an algorithm to align temporal sequences with possible local non-linear distortions, and has been widely applied to audio, video and graphics data alignments. DTW is essentially a point-to-point matching method…

计算机视觉与模式识别 · 计算机科学 2016-06-07 Jiaping Zhao , Laurent Itti

Many applications generate and consume temporal data and retrieval of time series is a key processing step in many application domains. Dynamic time warping (DTW) distance between time series of size N and M is computed relying on a dynamic…

数据库 · 计算机科学 2012-08-02 K. Selçuk Candan , Rosaria Rossini , Maria Luisa Sapino , Xiaolan Wang

Dynamic Time Warping (DTW) has become the pragmatic choice for measuring distance between time series. However, it suffers from unavoidable quadratic time complexity when the optimal alignment matrix needs to be computed exactly. This…

机器学习 · 计算机科学 2023-06-02 Fabian Latorre , Chenghao Liu , Doyen Sahoo , Steven C. H. Hoi

Many real-world applications require aligning two temporal sequences, including bioinformatics, handwriting recognition, activity recognition, and human-robot coordination. Dynamic Time Warping (DTW) is a popular alignment method, but can…

机器学习 · 计算机科学 2021-09-21 Sridhar Mahadevan , Anup Rao , Georgios Theocharous , Jennifer Healey

This paper addresses learning end-to-end models for time series data that include a temporal alignment step via dynamic time warping (DTW). Existing approaches to differentiable DTW either differentiate through a fixed warping path or apply…

机器学习 · 计算机科学 2023-03-21 Ming Xu , Sourav Garg , Michael Milford , Stephen Gould

Modern applications such as voice recognition rely on the ability to compare signals to pre-recorded ones to classify them. However, this comparison typically needs to ignore differences due to signal noise, temporal offset, signal…

机器学习 · 计算机科学 2022-06-16 Arvind Seshan

In this work, we explore the problem of aligning two time-ordered point clouds which are spatially transformed and re-parameterized versions of each other. This has a diverse array of applications such as cross modal time series…

计算机视觉与模式识别 · 计算机科学 2017-11-22 Christopher J. Tralie

Feature based visual odometry and SLAM methods require accurate and fast correspondence matching between consecutive image frames for precise camera pose estimation in real-time. Current feature matching pipelines either rely solely on the…

计算机视觉与模式识别 · 计算机科学 2020-08-03 Patrick Ruhkamp , Ruiqi Gong , Nassir Navab , Benjamin Busam

The stability of mine dumps is contingent upon the precise arrangement of spoil piles, taking into account their geological and geotechnical attributes. Yet, on-site characterisation of individual piles poses a formidable challenge. The…

计算机视觉与模式识别 · 计算机科学 2025-05-21 Sureka Thiruchittampalam , Bikram P. Banerjee , Nancy F. Glenn , Simit Raval

Pointwise matches between two time series are of great importance in time series analysis, and dynamic time warping (DTW) is known to provide generally reasonable matches. There are situations where time series alignment should be invariant…

计算机视觉与模式识别 · 计算机科学 2015-05-26 Tsu-Wei Chen , Meena Abdelmaseeh , Daniel Stashuk

Here we present an automated method for obtaining wavelength calibrations for one-dimensional spectra, using Dynamic Time Warping (DTW). DTW is a flexible and well-understood algorithm for pattern matching, which has not been widely used in…

A novel image matching method is proposed that utilizes learned features extracted by an off-the-shelf deep neural network to obtain a promising performance. The proposed method uses pre-trained VGG architecture as a feature extractor and…

计算机视觉与模式识别 · 计算机科学 2021-06-16 Ufuk Efe , Kutalmis Gokalp Ince , A. Aydin Alatan

LiDAR odometry is a fundamental task for various areas such as robotics, autonomous driving. This problem is difficult since it requires the systems to be highly robust running in noisy real-world data. Existing methods are mostly local…

计算机视觉与模式识别 · 计算机科学 2020-04-10 Zhichao Li , Naiyan Wang

Recent automated crop mapping via supervised learning-based methods have demonstrated unprecedented improvement over classical techniques. However, most crop mapping studies are limited to same-year crop mapping in which the present year's…

机器学习 · 计算机科学 2019-11-28 Mustafa Teke , Yasemin Yardımcı

Dynamic time warping (DTW) is a robust similarity measure of time series. However, it does not satisfy triangular inequality and has high computational complexity, severely limiting its applications in similarity search on large-scale…

信息检索 · 计算机科学 2020-02-12 Zhengxin Li

In this proof of concept, we use Computer Vision (CV) methods to extract pose information out of exercise videos. We then employ a modified version of Dynamic Time Warping (DTW) to calculate the deviation from a gold standard execution of…

计算机视觉与模式识别 · 计算机科学 2023-10-16 Sebastian Dill , Maurice Rohr

Template matching is a fundamental task in computer vision and has been studied for decades. It plays an essential role in manufacturing industry for estimating the poses of different parts, facilitating downstream tasks such as robotic…

计算机视觉与模式识别 · 计算机科学 2024-08-21 Zhirui Gao , Renjiao Yi , Zheng Qin , Yunfan Ye , Chenyang Zhu , Kai Xu

Emerging applications in Printed Circuit Board (PCB) routing impose new challenges on automatic length matching, including adaptability for any-direction traces with their original routing preserved for interactiveness. The challenges can…

硬件体系结构 · 计算机科学 2024-07-30 Weijie Fang , Longkun Guo , Jiawei Lin , Silu Xiong , Huan He , Jiacen Xu , Jianli Chen

Full Waveform Inversion (FWI) is a powerful technique for estimating high-resolution subsurface velocity models by minimizing the discrepancy between modeled and observed seismic data. However, the oscillatory nature of seismic waveforms…

Rapid generation of large-scale orthoimages from Unmanned Aerial Vehicles (UAVs) has been a long-standing focus of research in the field of aerial mapping. A multi-sensor UAV system, integrating the Global Positioning System (GPS), Inertial…

计算机视觉与模式识别 · 计算机科学 2025-03-06 Jialei He , Zhihao Zhan , Zhituo Tu , Xiang Zhu , Jie Yuan
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