Evaluation Study on Semantic Object Labelling in Street Scenes

By Andreas Wittmann, Margrit Gelautz, and Florian Seitner

Abstract

We present a processing pipeline for semantic scene labelling that was developed in view of autonomous driving applications. Our study focuses on two different methods for feature selection - Texture-layout-filter (TLF) and Single Histogram Class Models (SHCM) - whose influence on the performance of a random forest classifier is investigated. In tests on the Cityscapes dataset, we assess the effects of parameter variation and observe an improvement of the Intersection over Union score by 44 percent when substituting the TLF by the computationally more demanding SHCM feature.

Reference

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BibTeX

@inproceedings{TUW-279580,     author = {Wittmann, Andreas and Gelautz, Margrit and Seitner, Florian},     title = {Evaluation Study on Semantic Object Labelling in Street Scenes},     booktitle = {Proceedings of the ARW {\&} OAGM Workshop 2019},     year = {2019},     pages = {201--202},     publisher = {Verlag der Technischen Universit{\"a}t Graz},     url = {https://publik.tuwien.ac.at/files/publik_279580.pdf},     isbn = {978-3-85125-663-5},     doi = {10.3217/978-3-85125-663-5-45},     keywords = {semantische Annotierung / Stra{\ss}enszenen / Kontextbasierte Feature / Texturbasierte Feature / SHCM Feature / Texture-layout-filter Feature},     note = {Vortrag: ARW {\&} OAGM Workshop 2019, Steyr; 2019-05-09 -- 2019-05-10} } Click into the text area and press Ctrl+A/Ctrl+C or ⌘+A/⌘+C to copy the BibTeX into your clipboard… or download the BibTeX.