Air Traffic Trajectories Segmentation Based on Time-Series Sensor Data

Guerrero, José Luis; García, Juan Francisco Blanco; Molina, José Manuel

doi:10.5772/9956

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Segmentation Of Trajectories1

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2013

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“…A number of spatio-temporal cut criteria are discussed by Buchin et al 23 Concerning performance, a variety of methods implementing such criteria have been proposed. [24][25][26][27] We use a slightly modified approach for segmentation as we are interested in regions where the movement of animals fulfills specific properties that label them as sleeping places or foraging areas.…”

Section: Segmentation Of Trajectoriesmentioning

confidence: 99%

Visual abstraction of complex motion patterns

et al. 2013

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Figure 1. In order to reveal hidden information and patterns in motion data (a), we propose two sequential techniques: the geospatial (b) and the temporal abstraction (c). The geospatial abstraction uses a density-based approach to cluster very dense areas based on user chosen properties. The temporal abstraction segments and visualizes the results of the geospatial abstraction as a graph network, represented in several small multiples. Through an interactive feedback loop the user is able to explore and analyze the trajectory.

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