A minimalistic toolbox for extracting features from sport activity files

Lukač, Luka; Rajšp, Alen; Fister, Iztok; Pečnik, Luka; Fister, Dušan

doi:10.1109/ines52918.2021.9512927

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…The verification procedure (Algorithm 1) receives a list of training records and a list of all intersections as parameters (line 1). The training records were parsed using The minimalistic toolbox for extracting features from sport activity files [46]. The outer for loop ensures that every training activity was processed (line 3-17), and the inner for loop (line 4-16) processed every individual recorded point of the individual training activity (GPX/TCX point).…”

Section: Data Fusionmentioning

confidence: 99%

A Modified Evolutionary Algorithm for Generating the Cycling Training Routes

Rajšp

Fister

2022

IEEE Access

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We present a novel method for generating cycling training routes from geographical property graphs based on an Evolutionary Algorithm. The algorithm operators of crossover and mutation are adjusted for use in the Property Graph domain. Data fusion of geographical data from the OpenStreetMap, EU-DEM digital surface model, and existing training records is performed as a basis of the intersections-paths' property graph. The proposed approach allows route generation based on their starting and ending points in the property graph and their distance and ascent. A property graph of all intersections and cycling roads is shown and generated for the regions of Podravje and Pomurje. The property graph used in the proposed algorithm's feasibility demonstration is shown. This is done by presenting four different cases of routes that were generated with our algorithm. The algorithm allows for generating classic cycling routes of A to B nature, routes with more than two fixed points, as well as cyclical training routes. The research is concluded by offering further directions on route generation research.

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Section: Data Fusionmentioning

confidence: 99%