Multicamera systems are widely used for virtual reality applications. Due to limited processing power and novel tools, many multicamera capturing systems focus on a small number of cameras that are perfectly aligned. Therefore, dealing with room-size multicamera systems remains a challenging research topic.

In the context of multicamera scene image acquisition, camera calibration relies on the detection and matching of interest points between images of neighboring views, allowing to retrieve the relative pose and properties of each camera. Due to different color responses of the cameras, the color correction or equalization among multiple views is also challenging. Moreover, in order to acquire video content, synchronization among cameras is crucial. In this project, we tackle such difficulties by setting up a room-size multicamera system.

LISA-VR has extensive expertise in developing several VR systems and related tools for Depth Image-based Rendering (DIBR) tools; such as Reference View Synthesizer (RVS), and Depth Estimation Reference Software (DERS). These tools are commonly used in international standardization activities.
The ideal candidate for this Master thesis is driven and a problem solver. The student wants to learn simulation techniques, hardware prototyping, and GPU programming. The student will be able to work in a dynamic team.

Prerequisites: programming experience (C++ and/or Python), familiarity with image processing is a plus.

Keywords: Image analysis and camera models

Promotor: Gauthier LAFRUIT (Gauthier.Lafruit@ulb.be)

Support: Yupeng Xie, Hamed Razavi Khosroshahi, Daniele Bonatto