Scientific Computing Seminar

Date and Place: Thursdays and hybrid (live in 32-349/online via Zoom). For detailed dates see below!

Content

In the Scientific Computing Seminar we host talks of guests and members of the SciComp team as well as students of mathematics, computer science and engineering. Everybody interested in the topics is welcome.

List of Talks

Event Information:

  • Wed
    26
    Jun
    2024

    SC Seminar: Daniel Maue

    9:00Room 32-349

    Daniel Maue, RPTU Kaiserslautern-Landau

    Title: Depth-Aware Traffic Sign Recognition – A Multi-Stage 3D Localization & Classification Pipeline for Traffic Signs

    Abstract:

    Recognizing objects within images is a key task in computer vision. There are many traditional algorithmic approaches for locating objects in images and with the rise of research of artificial intelligence also deep learning recognition models were proposed. State-of-the-art methods already achieve matching or better performance than humans. The goal of this thesis is to give the common recognition task a third dimension, by not only locating objects in the 2D image but also estimating the depth of this object within the captured scene. Especially traffic sign recognition would benefit from the additional depth information, since capturing the distance and thus the order of oncoming traffic signs could greatly improve safety in vehicles since the depth can have important semantic meanings to the current and future driver assistance system. Therefore this bachelor thesis focuses on proposing a multi-stage 3D localization pipeline for traffic signs, by thoroughly analyzing and comparing state-of-the-art methods in object recognition and depth estimation. With that, these two topics are first introduced by covering related work and the needed theoretical background. Additionally, the considered approaches for object recognition and depth estimation are explained and finally evaluated in experiments, to find the most suitable methods for a 3D localization pipeline.