| Summary: | The aim of this work was to determine whether line-type features(straight lines found in geometry considered interesting by auser) could be identified in spatial map data of indoorenvironments produced by the Microsoft Hololens augmented realityheadset. Five different data sets were used in this work onwhich the feature detection was performed, these data sets wereprovided as sample data representing the spatial map of fivedifferent rooms scanned using the Hololens headset which areavailable as part of the Hololens emulator. Related work onfeature detection in point clouds and 3D meshes were investigatedto try and find a suitable method to achieve line-type featuredetection. The chosen detection method used LSQ-plane fitting andrelevant cutoff variables to achieve this, which was inspired byrelated work on the subject of feature identification and meshsimplification. The method was evaluated using user-placedvalidation features and the distance between them and the detectedfeatures, defined using the midpoint diistance metric was used asa measure of quality for the detected measures. The resultingfeatures were not accurate enough to reliably or consistentlymatch the validation features inserted in the data and furtherimprovements to the detection method would be necessary to achievethis. A local feature-edge detection using the SOD & ESODoperators was considered and tested but was found to not besuitable for the spatial data provided by the Hololens emulator.The results shows that finding these features using the provideddata is possible, and the methods to produce them numerous. Thechoice of mehtod is however dependent on the ultimate applicationof these features, taking into account requirements for accuracyand performance.
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