Lukas Polok

• MSc, Ph.D.
• Researcher at Brno University of Technology

Efficient algorithms exist to obtain a sparse 3D representation of the environment. Bundle adjustment (BA) and structure from motion (SFM) are techniques used to estimate both the camera poses and the set of sparse points in the environment. Many applications require such reconstruction to be performed online, while acquiring the data, and produce...

Solving large linear systems is a fundamental task in many interesting problems, including finite element methods (FEM) or (non-)linear least squares (NLS), among others. Furthermore, the problems of interest here are sparse: not all the vertices in a typical FEM mesh are connected, or similarly not all vertices in a graphical inference model are l...

This thesis focuses on data structures for sparse block matrices and the associated algorithms for performing linear algebra operations that I have developed. Sparse block matrices occur naturally in many key problems, such as Nonlinear LEast Squares (NLS) on graphical models. NLS are used by e.g. Simultaneous Localization and Mapping (SLAM) in rob...

The most common way to deal with the uncertainty present in noisy sensorial perception and action is to model the problem with a probabilistic framework. Maximum likelihood estimation is a well-known estimation method used in many robotic and computer vision applications. Under Gaussian assumption, the maximum likelihood estimation converts to a no...

Maximum likelihood estimation (MLE) is a well-known estimation method used in many robotic and computer vision applications. Under Gaussian assumption, the MLE converts to a nonlinear least squares (NLS) problem. Efficient solutions to NLS exist and they are based on iteratively solving sparse linear systems until convergence. In general, the exist...

3D reconstruction has a wide variety of applications in computer graphics, robotics or digital cinema production, among others. With the rapid increase in computing power, it has become more feasible for the reconstruction algorithms to run online, even on mobile devices. Maximum likelihood estimation (MLE) is the adopted technique to deal with the...

This paper deals with the impact the architectural changes of modern GPUs have on their use in scientific computing. It particularly focuses on significant drops in the number of double precision functional units in NVIDIA Maxwell architecture. Proposed remedies of the potential negative impact on GPGPU applications that are based on multiple preci...

A typical high-end film production generates several terabytes of data per day, either as footage from multiple cameras or as background information regarding the set (laser scans, spherical captures, etc). This paper presents solutions to improve the integration of the multiple data sources, and understand their quality and content, which are usef...

In the modern digital cinema production, extremely large volumes (in order of 10s of TB) of footage data are captured every day. The process of cataloging and reviewing such footage is nowadays largely manual and time consuming process. In our work, we aim at technical quality aspects, such as correct exposure, color compatibility of adjacent shots...

Modern digital film production uses large quantities of data captured on-set, such as videos, digital photographs, LIDAR scans, spherical photography and many other sources to create the final film frames. The processing and management of this massive amount of heterogeneous data consumes enormous resources. We propose an integrated pipeline for 2D...

A typical high-end film production generates several terabytes of data per day, either as footage from multiple cameras or as background information regarding the set (laser scans, spherical captures, etc). The EU project IMPART (impart.upf.edu) has been researching solutions that improve the integration and understanding of the quality of the mult...

Modern digital film production uses large quantities of data captured on-set, such as videos, digital photographs, LIDAR scans, spherical photography and many other sources to create the final film frames. The processing and management of this massive amount of heterogeneous data consumes enormous resources. We propose an integrated pipeline for 2D...

Many estimation problems in robotics rely on efficiently solving nonlinear least squares (NLS). For example, it is well known that the simultaneous localisation and mapping (SLAM) problem can be formulated as a maximum likelihood estimation (MLE) and solved using NLS, yielding a mean state vector. However, for many applications recovering only the...

A typical high-end film production generates several terabytes of data per day, either as footage from multiple cameras or as background information regarding the set (laser scans, spherical captures, etc). The EU project IMPART (impart.upf.edu) has been researching solutions that improve the integration and understanding of the quality of the mult...

Realistic 3D models of the environment are beneficial in many fields, from natural or man-made structure inspection and volumetric analysis, to movie-making, in particular, special effects integration to natural scenes. Spherical cameras are becoming popular in environment modelling because they capture the full surrounding scene visible from the c...

Sparse matrix multiplication is an important algorithm in a wide variety of problems, including graph algorithms, simulations and linear solving to name a few. Yet, there are but a few works related to acceleration of sparse matrix multiplication on a GPU. We present a fast, novel algorithm for sparse matrix multiplication, outperforming the previo...

Realistic 3D models of the environment are beneficial in many fields, from natural or man-made structure inspection and volumetric analysis, to movie-making, in particular, special effects integration to natural scenes. Spherical cameras are becoming popular in environment modelling because they capture the full surrounding scene visible from the c...

Accurate online estimation of the structure of the environment together with the pose of the robot is an important component to enable autonomous robotic applications. This paper analyses the different parameterisations used in structure from motion (SFM) problem in the context of accuracy and efficiency of the on-line solutions. Three point parame...

Fast sorting is an important step in many parallel algorithms, which require data ranking, ordering or partitioning. Parallel sorting is a widely researched subject, and many algorithms were developed in the past. In this paper, the focus is on implementing highly efficient sorting routines for the sparse linear algebra operations, such as parallel...

Online applications in robotics, computer vision, and computer graphics rely on efficiently solving the associated nolinear systems every step. Iteratively solving the non-linear system every step becomes very expensive if the size of the problem grows. This can be mitigated by incrementally updating the linear system and changing the linearization...

Abstract —Efficiently solving nonlinear least squares (NLS) problems is crucial for many applications in robotics. In online applications, solving the associated nolinear systems every step may become very expensive. This paper introduces online, incremental solutions, which take full advantage of the sparse- block structure of the problems in robo...

A large number of robotic, computer vision and computer graphics applications rely on efficiently solving the associated sparse linear systems. Simultaneous localization and mapping (SLAM), structure from motion (SfM), non-rigid shape recovery, and elastodynamic simulations are only few examples in this direction. In general, these problems are non...

Efficiently manipulating and operating on block matrices can be beneficial in many applications, among others those involving iteratively solving nonlinear systems. These types of problems consist of repeatedly assembling and solving sparse linear systems. In the case of very large systems, without a careful manipulation of the corresponding matric...

Nowadays, the flight guidance equipment supplies practically all the information, required for aircraft navigation. Pseudo-realistic terrain visualization is undoubtedly an important part of this information. Although modern graphics processors are able to render realistic terrain at interactive frame rates, in some applications, it is beneficial t...

GPUs have been successfully used for acceleration of many mathematical functions and libraries. A common limitation of those libraries is a minimal size of primitives being handled in order to achieve significant speedups compared to their CPU versions. The minimal size requirement can prove prohibitive for many applications. It can be loosened by...

Vector space models have received a significant attention in recent years. They have been applied in a wide spectrum of areas including information filtering, information retrieval, document indexing and relevancy ranking. Random indexing is one of the methods employing distributional statistics of term co-occurrences to generate vector space model...

This contribution presents the Local Rank Differences/Patterns low-level image feature extractor and its efficient implementations on several hardware architectures. This image feature set was not only developed to provide equal classification performance as its stateof-the-art alternatives, but to be executed much more efficiently in hardware impl...

A currently popular trend in object detection and pattern recognition is usage of statistical classifiers, namely AdaBoost and its modifications. The speed performance of these classifiers largely depends on the low level image features they are using: both on the amount of information the feature provides and the executional time of its evaluation...