Master Thesis “Implementation Of A Combined Multi-View Laser Line 3D Reconstruction System”

Universities and Institutes of Austria
October 19, 2022
Offerd Salary:Negotiation
Working address:N/A
Contract Type:Temporary
Working Time:Part time
Working type:N/A
Job Ref.:N/A
  • Organisation/Company: AIT Austrian Institute of Technology GmbH
  • Research Field: Computer science Mathematics Physics
  • Researcher Profile: First Stage Researcher (R1)
  • Application Deadline: 19/10/2022 21:00 - Europe/Brussels
  • Location: Austria › Vienna
  • Type Of Contract: Temporary
  • Job Status: Part-time
  • Hours Per Week: 20
  • We are Austria's largest research and technology organisation and an international player in applied research for innovative infrastructure solutions. This makes us a powerful development partner for industry and a top employer in the scientific community. Our Center for Vision, Automation & Control in Vienna invites applications for a:

    Master Thesis “Implementation of a combined multi-view laser line 3D reconstruction system”

    - Center for Vision, Automation & Control -


  • The inline computational imaging (ICI) technique of our Competence Unit High-Performance Vision Systems (HVS) is based on a single-image sensor technology including corresponding algorithms for image reconstruction, for simultaneous 2D and 3D quality inspection of manufactured parts. Our ICI pipeline reconstructs the acquired object in 3D by applying a multi-view stereo algorithm, by finding the same features/patterns in multiple images. This is only possible if the object exhibits some surface texture, such as banknotes, wafers, or steel billets for instance. This is not the case for objects that are rather smooth, such as keys for instance, at spatial resolutions at which they are analyzed.
  • On this account, this master's thesis project will take a step towards a new “Laser-augmented ICI”, which extends the current standard setup for ICI by an additional laser line illumination. In presence of an object the laser line is bent by the object's surface to various degrees (as seen by the camera's sensor), depending on the local surface curvature. This distortion of the initially straight laser line can be used to infer spatially resolved depth information of the surface, even for objects without inherent surface texture. Including this extra depth cue into the reconstruction algorithms of the ICI pipeline would allow the inspection of objects more reliably, which exhibit no significant inherent surface texture at relevant length scales for the inspection task.

  • The main goal of this master's thesis is to investigate and evaluate the potential improvement of the 3D reconstruction quality, that can be gained with a new “Laser-augmented ICI” compared to standard ICI. The working hypothesis to be addressed in this work is whether additional laser line illumination and derived depth cues thereof improve the accuracy of the 3D reconstruction inferred from the acquired data. The basis of this work is a portable ICI setup that has been developed within a previous master's thesis.
  • To this end, the following specific aims are proposed:
  • (1) Literature research of the state-of-the art of laser line triangulation methods. This results in:​
  • Design and specifications of the extended “Laser-augmented ICI” setup (i.e., additional laser line illumination).
  • A selection of candidate laser line-based 3D reconstruction algorithms that infer depth information by analysing the distortion of a laser line.
  • (2) Extension of an available ICI setup to “Laser ICI”. This includes:
  • Adjusting an available ICI setup according to the designs/specifications from specific aim (1).
  • Acquiring laser line image data that is registered with the ICI image stacks.
  • Adapting and/or implementing candidate laser line-based 3D reconstruction algorithms identified in specific aim (1).
  • 3D reconstructing of the acquired data laser line-based 3D reconstruction algorithms. Ideally, this will be extended to a combined approach that uses the multi-view stereo approach (e.g., standard ICI) and laser-based depth cues at the same time.
  • (3) Evaluation of the selected laser-based 3D reconstruction approaches, by:
  • Defining and implementing figure of merits to evaluate the accuracy of 3D measurements from standard ICI and “Laser-augmented ICI” data.
  • Collecting image data for ground truth test objects, i.e., objects with known geometry.
  • Comparing the (added) benefit of the laser-based 3D reconstruction approaches with each other.
  • Benchmarking 3D reconstruction results of the selected test objects from “Standard ICI” and “Laser-augmented ICI”.​
  • Your project involves hands-on lab work, namely image acquisition of data sets and extension/adjustment of available imaging setups.
  • Furthermore, it entails practical programming work, i.e., the adaptation and/or implementation of laser-based 3D reconstruction algorithms and existing image acquisition software.
  • Finally, there will be testing of those algorithms and evaluating the resulting 3D reconstructions to assess the performance and added benefit of laser line illumination.

  • We expect that laser illumination and its additional depth cues will benefit the 3D reconstruction for objects with marginal inherent surface texture. The multi-view stereo matching algorithm, which is a core element of our ICI 3D reconstruction pipeline, requires surface texture to work reliably. In theory, the additional laser-based depth cue should be independent of the object's surface texture, and hence, is expected to improve the 3D reconstruction quality.
  • You will get familiar with state-of-the-art 3D reconstruction methods that are at the forefront of application-driven research in the field.
  • You have the unique opportunity to work on an interesting real-world problem that arose in ongoing collaborations with industrial partners. The Competence Unit High-Performance Vision Systems (HVS) at AIT has been active in research for industrial inspection and quality assurance systems for over 20 years, which creates a stimulating and supportive framework for the students working with us.
  • Your qualifications as an Ingenious Partner :

  • Ongoing Master's studies in Computer Vision/Image Processing, Computer Science, Physics, Mathematics or similar
  • Hands-on lab work experience with image acquisition using industrial/digital imaging is advantageous
  • Programming skills in Python and C++ are expected
  • Strong skills in image processing are expected
  • Knowledge about Blender are advantageous
  • Interest in technology development and applied research driven by real- world problems is expected
  • Good communications skills and ability to work in a multidisciplinary team are necessary
  • Very good command of English (in writing) is expected
  • What to expect:

    EUR 828,-- gross per month for 20 hours/week based on the collective agreement. There will be additional company benefits. You will be part of our international Young AIT network. As a research institution, we are familiar with the supervision and execution of master' theses, and we are looking forward to supporting you accordingly

    At AIT, the promotion of women is important to us - that's why we are especially looking forward to applications from female students!

    Please submit your application documents including CV, cover letter and certificates (transcript of records and other relevant certificates) online.

    TOMORROW TODAY - WITH YOU? Contact Information
  • Organisation/Company: AIT Austrian Institute of Technology GmbH
  • Department: Human Resources
  • Organisation Type: Public Research Institution
  • Website: https:// www.
  • Country: Austria
  • City: Vienna
  • Postal Code: 1210
  • Street: Giefinggasse 4
  • From this employer

    Recent blogs

    Recent news