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A computer vision approach for trajectory classification
2021 22nd IEEE International Conference on Mobile Data Management (MDM), 2021Nowadays, the increasing number of moving objects tracking sensors, results in the continuous flow of high-frequency and high-volume data streams. This phenomenon can especially be observed in the maritime domain since most of the vessels worldwide are now transmitting their positions periodically.
Ioannis Kontopoulos +3 more
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Vehicle Trajectory Approximation and Classification
Procedings of the British Machine Vision Conference 1998, 1998We present a variational technique for finding low curvature smooth approximations to trajectories in the plane. The method is applied to short segments of a vehicle trajectory in a known ground plane. Estimates of the speed and steering angle are obtained for each segment and the motion during the segment is assigned to one of the four classes: ahead,
Roberto Fraile, Stephen J. Maybank
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Trajectory Profiler Classification
IFAC Proceedings Volumes, 2000Abstract This paper will focus on the quality and the design issues of trajectory generation. The use of the profiler in the motion generation will be defined and different profiler classes will be presented. At the end, profilers will be classified according to the acceleration formula.
Mirko Boric, Ilan Cohen
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Private Trajectory Data Publication for Trajectory Classification
2019Trajectory classification (TC), i.e., predicting the class labels of moving objects based on their trajectories and other features, has many important real-world applications. Private trajectory data publication is to anonymize trajectory data, which can be released to the public or third parties.
Huaijie Zhu +4 more
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Segmentation Optimization in Trajectory-Based Ship Classification
Journal of Computational Science, 2020This research was funded by public research projects of Spanish Ministry of Economy and Competitivity (MINECO), reference TEC2017–88048-C2–2-R and by the Madrid Government under the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M17), and in the context of the V PRICIT (Regional Program of Research and ...
Daniel Amigo 0001 +3 more
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Incorporating Duration Information for Trajectory Classification
2012 IEEE 28th International Conference on Data Engineering, 2012Trajectory classification has many useful applications. Existing works on trajectory classification do not consider the duration information of trajectory. In this paper, we extract duration-aware features from trajectories to build a classifier. Our method utilizes information theory to obtain regions where the trajectories have similar speeds and ...
Dhaval Patel 0002 +3 more
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A Survey and Comparison of Trajectory Classification Methods
2019 8th Brazilian Conference on Intelligent Systems (BRACIS), 2019In trajectory classification tasks, the challenge is to find the subtrajectories or a set of features that better discriminate the class. However, there is a lack of robustness in existing methods, as they do not use the same datasets or do not compare their results with the state of the art.
Vania Bogorny +2 more
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Model-Based Classification of Trajectories
2015We present algorithms for classifying trajectories based on a movement model parameterized by a single parameter, like the Brownian bridge movement model. Classification is the problem of assigning trajectories to classes of similar movement characteristics.
Maike Buchin, Stef Sijben
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Unequal intra‐group variance in trajectory classification
Statistics in Medicine, 2018Classifying patients into groups according to longitudinal series of measurements (ie, trajectory classification) has become frequent in clinical research. Most classification models suppose an equal intra‐group variance across groups. This assumption is sometimes inappropriate because measurements in diseased subjects are often more heterogeneous than
Klich, Amna +2 more
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Trajectory clustering using mixed classification models
Statistics in Medicine, 2021Trajectory classification has become frequent in clinical research to understand the heterogeneity of individual trajectories. The standard classification model for trajectories assumes no between‐individual variance within groups. However, this assumption is often not appropriate, which may overestimate the error variance of the model, leading to a ...
Klich, Amna +2 more
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