Human motion trajectory prediction: A survey

A Rudenko, L Palmieri, M Herman… - … Journal of Robotics …, 2020 - journals.sagepub.com
With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …

Time-series clustering–a decade review

S Aghabozorgi, AS Shirkhorshidi, TY Wah - Information systems, 2015 - Elsevier
Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

A comparative analysis of trajectory similarity measures

Y Tao, A Both, RI Silveira, K Buchin… - GIScience & Remote …, 2021 - Taylor & Francis
Computing trajectory similarity is a fundamental operation in movement analytics, required
in search, clustering, and classification of trajectories, for example. Yet the range of different …

A review of moving object trajectory clustering algorithms

G Yuan, P Sun, J Zhao, D Li, C Wang - Artificial Intelligence Review, 2017 - Springer
Clustering is an efficient way to group data into different classes on basis of the internal and
previously unknown schemes inherent of the data. With the development of the location …

Intelligent multi-camera video surveillance: A review

X Wang - Pattern recognition letters, 2013 - Elsevier
Intelligent multi-camera video surveillance is a multidisciplinary field related to computer
vision, pattern recognition, signal processing, communication, embedded computing and …

A comparison study on similarity and dissimilarity measures in clustering continuous data

AS Shirkhorshidi, S Aghabozorgi, TY Wah - PloS one, 2015 - journals.plos.org
Similarity or distance measures are core components used by distance-based clustering
algorithms to cluster similar data points into the same clusters, while dissimilar or distant …

An unsupervised learning method with convolutional auto-encoder for vessel trajectory similarity computation

M Liang, RW Liu, S Li, Z **_Algorithm_Review/links/02bfe5100f11a7929f000000/Dynamic-Time-War**-Algorithm-Review.pdf" data-clk="hl=es&sa=T&oi=gga&ct=gga&cd=7&d=15187052104820319229&ei=MBOvZ6CtF9qy6rQP56ab0AE" data-clk-atid="_eMpxWw_w9IJ" target="_blank">[PDF] researchgate.net

[PDF][PDF] Dynamic time war** algorithm review

P Senin - … and Computer Science Department University of …, 2008 - researchgate.net
The Dynamic Time War** algorithm (DTW) is a well-known algorithm in many areas.
While first introduced in 60s [1] and extensively explored in 70s by application to the speech …

Spatiotemporal data mining: A computational perspective

S Shekhar, Z Jiang, RY Ali, E Eftelioglu, X Tang… - … International Journal of …, 2015 - mdpi.com
Explosive growth in geospatial and temporal data as well as the emergence of new
technologies emphasize the need for automated discovery of spatiotemporal knowledge …

Trajectory learning for activity understanding: Unsupervised, multilevel, and long-term adaptive approach

BT Morris, MM Trivedi - IEEE transactions on pattern analysis …, 2011 - ieeexplore.ieee.org
Society is rapidly accepting the use of video cameras in many new and varied locations, but
effective methods to utilize and manage the massive resulting amounts of visual data are …