János Márk Szalai-Gindl

Loading static point data into a system of shared-nothing machines is the focus of this research. The methods are histogram-based data placement strategies. In order to compare these strategies, performance measures were introduced, the examination of which is part of the research.

Keywords

Database Management, Information Search and Retrieval, optimization, Models of Computation

Point cloud template matching

The focus of the research is on finding the occurrences of template point cloud in another point cloud. Part of the task is to store large point clouds in a database and index them.

Keywords

Image Processing and Computer Vision, Pattern Recognition, Database managament, Information Search and Retrieval

Genomic database

The focus of the research is to store biological sequences, DNAs and index them, respectively, to speed up typical queries.

Keywords

Database Management

Highlighted publications

2021 – Varga, Daniel et al. – Template Matching for 3D Objects in Large Point Clouds Using DBMS – mtmt.hu
2017 – János, M Szalai-Gindl; László, Dobos; István, Csabai – Tiling Strategies for Distributed Point Cloud Databases – mtmt.hu
2022 – Varga, Daniel; Szalai-Gindl, Janos Mark; Ambrus-Dobai, Marton; Laki, Sandor – QBB: Quantile-Based Binarization of 3D Point Cloud Descriptors – mtmt.hu
2018 – Csabai, István; Dobos, László; Kiss, Attila; M. Szalai-Gindl, János – Some mathematical properties of the performance measures applied for point cloud databases – mtmt.hu
2024 – Szalai-Gindl, János Márk; Varga, Dániel – FPFH Revisited: Histogram Resolutions, Improved Features, and Novel Representation – mtmt.hu