Mariusz Oszust

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Verified

Mariusz verified their affiliation via an institutional email.

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• PhD DSc
• Professor (Associate) at Rzeszów University of Technology

The recent growth of multimedia content used in daily-life communication requires the development of image description techniques able to unequivocally identify observed objects, despite image transformations, demanding lighting conditions, or noise. This paper focuses on binary feature descriptors which are often used for this purpose. They have s...

The reception of multimedia applications often depends on the quality of processed and displayed visual content. This is the main reason for the development of automatic image quality assessment (IQA) techniques which try to mimic properties of human visual system and produce objective scores for evaluated images. Most of them require a training st...

The proliferation of electronic means of communication entails distortion of visual information carried by processed images. Therefore, automatic evaluation of image perceptual quality in a way that is consistent with human perception is important. In this letter, an approach to full-reference image quality assessment (IQA) is proposed. The percept...

Binary descriptors have become popular in many vision-based applications, as a fast and efficient replacement of floating point, heavy counterparts. They achieve a short computation time and low memory footprint due to many simplifications. Consequently, their robustness against a variety of image transformations is lowered, since they rely on pair...

Pan-Sharpening (PS) techniques aim to enhance the spatial resolution of low-resolution multispectral images by leveraging data from high-resolution panchromatic images. Their comparison typically relies on the quality assessment of the resulting Full-Resolution (FS) pan-sharpened images. However, in the absence of a reference image, a dedicated No-...

In this paper, a method for time series augmentation, aiming at the improvement of human action recognition accuracy of a deep learning classifier, is proposed. The approach performs time-scale modifications of the input time series and transforms them into compact sequences of time segments using Piecewise Aggregate Approximation (PAA) to facilita...

In this paper, an approach to augment action recognition time series datasets, devoted to improving the accuracy of deep learning classifiers, is proposed. In the introduced method, two operators are sequentially introduced that perform linear and nonlinear modifications in the time scale of the input time series. The resulting data samples contrib...

High-quality data is necessary for modern machine learning. However, the acquisition of such data is difficult due to noisy and ambiguous annotations of humans. The aggregation of such annotations to determine the label of an image leads to a lower data quality. We propose a data-centric image classification benchmark with nine real-world datasets...

No-reference image quality assessment (NR-IQA) methods automatically and objectively predict the perceptual quality of images without access to a reference image. Therefore, due to the lack of pristine images in most medical image acquisition systems, they play a major role in supporting the examination of resulting images and may affect subsequent...

Magnetic resonance (MR) imaging provides a large amount of data that requires a visual inspection before a diagnosis can be made. Since the exclusion of low-quality image sequences is performed manually and image processing methods are evaluated using techniques developed for natural images, automatic and reliable MR image quality assessment (IQA)...

The popularity of action recognition (AR) approaches and the need for improvement of their effectiveness require the generation of artificial samples addressing the nonlinearity of the time-space, scarcity of data points, or their variability. Therefore, in this paper, a novel approach to time series augmentation is proposed. The method improves th...

The Pan-Sharpening (PS) techniques provide a better visualization of a multi-band image using the high-resolution single-band image. To support their development and evaluation, in this paper, a novel, accurate, and automatic No-Reference (NR) PS Image Quality Assessment (IQA) method is proposed. In the method, responses of two complementary networ...

The recently introduced Marine Predators Algorithm (MPA) exhibits competitive performance in solving optimization problems. However, it often prematurely converges due to an imbalance between its exploration and exploitation capabilities. Therefore, in this paper, an improved MPA variant using a proposed Local Escaping Operator (LEO) is introduced....

The recent proliferation of population-based meta-heuristics designed for solving optimization problems and their successes confirm that more promising techniques inspired by physical phenomena or biological systems are desired. Therefore, in this paper, a novel hybridization approach is proposed to improve the performance of optimization algorithm...

In this paper, an approach to isolated sign language recognition with data provided by a depth camera is presented. In the introduced method, sequences of depth maps of dynamic sign language gestures are divided into smaller regions (cells). Then, statistical information is used to describe the cells. Since gesture executions have different lengths...

The quality of magnetic resonance images may influence the diagnosis and subsequent treatment. Therefore, in this paper, a novel no-reference (NR) magnetic resonance image quality assessment (MRIQA) method is proposed. In the approach, deep convolutional neural network architectures are fused and jointly trained to better capture the characteristic...

The development of digital image processing techniques requires reliable image quality assessment (IQA) methods. Since images acquired by a camera often contain various distortions and their non-distorted versions are not available, a no-reference IQA (NR-IQA) technique should be used. Many popular methods are developed to assess artificially disto...

Markov-type inequalities are often used in numerical solutions of differential equations, and their constants improve error bounds. In this paper, the upper approximation of the constant in a Markov-type inequality on a simplex is considered. To determine the constant, the minimal polynomial and pluripotential theories were employed. They include a...

Background: The perceptual quality of magnetic resonance (MR) images influences diagnosis and may compromise the treatment. The purpose of this study was to evaluate how the image quality changes influence the interobserver variability of their assessment. Methods: For the variability evaluation, a dataset containing distorted MRI images was pre...

An investigation of diseases using magnetic resonance (MR) imaging requires automatic image quality assessment methods able to exclude low-quality scans. Such methods can be also employed for an optimization of parameters of imaging systems or evaluation of image processing algorithms. Therefore, in this paper, a novel blind image quality assessmen...

Purpose Subjective quality assessment of displayed magnetic resonance (MR) images plays a key role in diagnosis and the resultant treatment. Therefore, this study aims to introduce a new no‐reference (NR) image quality assessment (IQA) method for the objective, automatic evaluation of MR images and compare its judgments with those of similar techni...

In this paper, a novel data augmentation method for time-series classification is proposed. In the introduced method, a new time-series is obtained in warped space between suboptimally aligned input examples of different lengths. Specifically, the alignment is carried out constraining the warping path and reducing its flexibility. It is shown that...

Image quality assessment (IQA) measures predict the perceived quality of evaluated images, aiming to replace time-consuming human evaluation. This is particularly important for the automatic comparison of image processing techniques which often modify image content. Since the presence of noise highly affects the perception of images and only a few...

Image processing methods often introduce distortions, which affect the way an image is subjectively perceived by a human observer. To avoid inconvenient subjective tests in cases in which reference images are not available, it is desirable to develop an automatic no-reference image quality assessment (NR-IQA) technique. In this paper, a novel NR-IQ...

In this letter, a novel Blind Image Quality Assessment (BIQA) technique is introduced to provide an automatic and reproducible evaluation of distorted images. In the approach, the information carried by image derivatives of different orders is captured by local features and used for the image quality prediction. Since a typical local feature descri...

SELECTED MANAGEMENT PROBLEMS IN A KNOWLEDGE-BASED ECONOMY - ENTREPRENEURSHIP AND BEHAVIOR INNOVATIVE

W rozdziale opisano proces komercjalizacji badań naukowych na przykładzie dwóch systemów wspomagających osoby z niepełnosprawnościami, SyKoMi i BlinkMouse. Pilotażowe rozwiązanie pierwszego z systemów, przygotowane w ramach grantu NCN i NCBiR "Tango", zostało zainstalowane w Urzędzie Miasta Rzeszowa, umożliwiając osobom głuchym posługującym się jęz...

Purpose This paper aims to present a vision-based method for determination of the position of a fixed-wing aircraft that is approaching a runway. Design methodology/approach The method determines the location of an aircraft based on positions of precision approach path indicator lights and approach light system with sequenced flashing lights in th...

The perceptual quality of images is often affected by applied image processing techniques. Their evaluation requires tests which involve human subjects. However, in most cases, image quality assessment (IQA) should be automatic and reproducible. Therefore, in this paper, a novel no-reference IQA method is proposed. The method uses high-order deriva...

Blind Image Quality Assessment (BIQA) techniques evaluate the perceptual quality of a distorted image without access to its distortion-free version. In this paper, a novel BIQA measure is proposed in which interest points drawn by visually attractive regions in a grayscale image are characterized using a binary descriptor. Then, a regression techni...

In this paper, an approach to the development of a localisation system for supporting visually impaired people is proposed. Instead of using unique visual markers or radio tags, this approach relies on image recognition with local feature descriptors. In order to provide fast and robust keypoint description, a new binary descriptor is introduced. T...

The aim of no-reference image quality assessment (NR-IQA) techniques is to measure the perceptual quality of an image without access to the reference image. In this letter, a novel NR-IQA measure is introduced in which quality-aware statistics are used as perceptual features for the quality prediction. In the method, the distorted image is converte...

The usage of real-valued, local descriptors in computer vision applications is often constrained by their large memory requirements and long matching time. Typical approaches to the reduction of their vectors map the descriptor space to the Hamming space in which the obtained binary strings can be efficiently stored and compared. In contrary to suc...

The advances in the development of imaging devices resulted in the need of an automatic quality evaluation of displayed visual content in a way that is consistent with human visual perception. In this paper, an approach to full-reference image quality assessment (IQA) is proposed, in which several IQA measures, representing different approaches to...

The desired local feature descriptor should be distinctive, compact and fast to compute and match. Therefore, many computer vision applications use binary keypoint descriptors instead of floating-point, rich techniques. In this paper, an optimisation approach to the design of a binary descriptor is proposed, in which the detected keypoint is descri...

Information carried by an image can be distorted due to different image processing steps introduced by different electronic means of storage and communication. Therefore, development of algorithms which can automatically assess a quality of the image in a way that is consistent with human evaluation is important. In this paper, an approach to image...

Gestures are natural means of communication between humans, and therefore their application would benefit to many fields where usage of typical input devices, such as keyboards or joysticks is cumbersome or unpractical (e.g., in noisy environment). Recently, together with emergence of new cameras that allow obtaining not only colour images of obser...

Detection of repeatable keypoints is often one of the first steps leading to obtain a solution able to recognise objects on images. Such objects are characterised by content of image patches indicated by keypoints. A given image patch is worth being described and processed in further steps, if the interest point inside of it can be found desp...

We focus on gesture recognition based on 3D information in the form of a point cloud of the observed scene. A descriptor of the scene is built on the basis of a Viewpoint Feature Histogram (VFH). To increase the distinctiveness of the descriptor the scene is divided into smaller 3D cells and VFH is calculated for each of them. A verification of the...

Depth cameras, such as time of flight (ToF) camera or Kinect are increasingly used for hand gesture recognition. In contrast to other works, based on hand segmentation, this paper takes into account the point cloud corresponding to the silhouette, from the waist up, of the person performing gestures. We propose using descriptor based on Viewpoint F...

The paper considers recognition of isolated Polish Sign Language words observed by Kinect. A whole word model approach with nearest neighbour classifier applying dynamic time warping (DTW) technique is compared with an approach using models of subunits, i.e. some elements smaller than words, resembling phonemes in spoken expressions. Such smaller m...

This paper considers automatic visual recognition of signed expressions. The proposed method is based on modelling gestures with subunits, which is similar to modelling speech by means of phonemes. To define the subunits a data-driven procedure is applied. The procedure consists in partitioning time series, extracted from video, into subsequences w...

Complexity of sign language recognition system grows with growing word vocabulary. Therefore it is advisable to use units smaller than words. Such elements, called subunits, resemble phonemes in spoken language. They are concatenated to form word models. We propose a data–driven procedure for finding subunits in time series representing signed expr...

Time-of-flight (ToF) cameras acquire 3D information about observed scenes. They are increasingly used for hand gesture recognition. This paper is also related to this problem. In contrast to other, hand segmentation based, works we propose using point cloud processing and the Viewpoint Feature Histogram (VFH) as the global descriptor of the scene....

Time-of-flight (ToF) cameras acquire 3D information about observed scenes. They are increasingly used for hand gesture recognition. This paper is also related to this problem. In contrast to other works which try to segment the hands we propose using point cloud processing and the Viewpoint Feature Histogram (VFH) as the global descriptor of the sc...

In this paper we present an approach to recognition of signed expressions based on visual sequences obtained with Kinect sensor. Two variants of time series representing the expressions are considered: the first based on skeletal im- ages of the body, and the second describing shape and po- sition of hands extracted as skin coloured regions. Time s...

The paper considers time series with known class labels representing 101 words of Polish sign language (PSL) performed many times in front of a camera. Three clustering algorithms: K–means, K–medoids and Minimum Entropy Clustering (MEC) are compared. Preliminary partitioning of the data set is performed with help of immune based optimisation. Some...

The paper considers Polish sign language (PSL) words recognition with sensor Kinect. The nearest neighbour classifier with dynamic time warping technique was examined. The classifier was using two sets of features, the first produced by Kinect (in a form of 3D positions of most important joints of observed person body — a skeletal image or a skelet...

The paper considers automatic vision based modelling and recognition of sign language expressions using smaller units than words. Modelling gestures with subunits is similar to modelling speech by means of phonemes. To define the subunits a data–driven procedure is proposed. The procedure consists in partitioning time series of feature vectors obta...

The paper presents a prototype of a system which can be used as a therapeutic and educational tool for children with developmental problems. Natural body movements and gestures are used in the system to interact with virtual objects displayed on the screen. Nowadays such systems can be built with the use of widely available free software tools for...

The paper considers automatic visual recognition of signed expressions. The proposed method is based on modeling gestures with subunits, which is similar to modeling speech by means of phonemes. To define the subunits a data-driven procedure is applied. The procedure consists in partitioning time series, extracted from video, into subsequences whic...

The paper considers partitioning time series into subsequences which form homogeneous groups. To determine the cut points an evolutionary optimization procedure based on multicriteria quality assessment of the resulting clusters is applied. The problem is motivated by automatic recognition of signed expressions, based on modeling gestures with subu...

The paper presents a prototype of a system which can be used as a therapeutic and educational tool for children with developmental problems. Natural body movements and gestures are used in the system to interact with virtual objects displayed on the screen. Nowadays such systems can be easily built with the use of widely available free software too...

The paper considers partitioning time series into subsequences which form homogeneous groups. To determine the cut points an evolutionary optimization procedure based on multicriteria quality assessment of the resulting clusters is applied. The problem is motivated by automatic recognition of signed expressions, based on modeling gestures with subu...

The mammal immune system is a distributed multiagent system. Its properties of distributive control and self organization have created interest in using immune principles to solve complex engineering tasks such as decentralized robot control, pattern recognition, multimodal and combinatorial optimization. In this paper a new immunity-based algorith...