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<p>The results presented in this contribution demonstrate the value of climate services for the planned construction of the new Wastewater Treatment Plant (WWTP) in Novi Sad, Serbia. In this case, climate services... more
<p>The results presented in this contribution demonstrate the value of climate services for the planned construction of the new Wastewater Treatment Plant (WWTP) in Novi Sad, Serbia. In this case, climate services provided added value for the decision-making processes, in terms of enhanced effectiveness, optimized technological opportunities and minimized risks and by serving as the means of involving and better-informing end-users and stakeholders. The specific goal of the research was to improve climate change resilience of the WWTP and to facilitate better overall hygienic conditions in Novi Sad and to safeguard the potable water resources and the quality of the environment in the areas located downstream and under the influence of the Danube River.</p> <p>In order to achieve it, preliminary activities were oriented on analyzing the current climate and hydrological conditions, engaging the relevant data providers, stakeholders and policy makers and evaluating what relevant local data would be useful for the study. The data collected was applied in the testing and for improving the Future Danube Multi-hazard, Multi-risk Model (FDM), a catastrophe model implemented in the OASIS Loss Modeling Framework (Oasis-LMF). The FDM is implemented for the entire Danube Basin. High-resolution components for pluvial flood risks were further implemented to the city of Novi Sad, Serbia, after successful testing in the Budapest region. Observations and model results were used in a climate change impact assessment with the purpose of identifying adaptation options, appraisal of adaptation options and integration of an adaptation action plan into the Feasibility Study of the WWTP construction. The results of the pluvial flood model for Novi Sad clearly suggested that it is important to consider pluvial flood risks and that protective measures have to be considered as part of the WWTP construction, both under current and future climate conditions. Moreover, novel estimates of drainage water intensities during heavy rains would advise the design of the simultaneously planned pumping station on the banks of the Danube. Combined, this clearly demonstrates the added value of the climate services and risk information delivered by the FDM also beyond the insurance sector, as well as its potential to support adaptation decision making with respect to infrastructural investments in Novi Sad.</p>
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This work describes an approach to calculate pedological parameter maps using hyperspectral remote sensing and soil sensors. These maps serve as information basis for automated and precise agricultural treatments by tractors and field... more
This work describes an approach to calculate pedological parameter maps using hyperspectral remote sensing and soil sensors. These maps serve as information basis for automated and precise agricultural treatments by tractors and field robots. Soil samples are recorded by a handheld hyperspectral sensor and analyzed in the laboratory for pedological parameters. The transfer of the correlation between these two data sets to aerial hyperspectral images leads to 2D-parameter maps of the soil surface. Additionally, rod-like soil sensors provide local 3D-information of pedological parameters under the soil surface. The goal is to combine the area-covering 2D-parameter maps with the local 3D-information to extrapolate large-scale 3D-parameter maps using AI approaches.
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Human strategies for solving the travelling salesperson problem (TSP) continue to draw the attention of the researcher community, both to further understanding of human decision-making and inspiration for the design of automated solvers.... more
Human strategies for solving the travelling salesperson problem (TSP) continue to draw the attention of the researcher community, both to further understanding of human decision-making and inspiration for the design of automated solvers. Online games represent an efficient way of collecting large amounts of human solutions to the TSP, and PathGame is a game focusing on non-Euclideanclosed-form TSP. To capture the instinctive decision-making process of the users, PathGame requires users to solve the problem as quickly as possible, while still favouring more efficient tours. In the initial study presented here, we have used PathGame to collect a dataset of over 16,000 tours, containing over 22,000,000 destinations. Our analysis of the data revealed new insights related to ways in which humans solve TSP and the time it takes them when forced to solve TSPs of large complexity quickly.
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The paper presents a system for automatic video surveillance based on paired cameras in a stereoscopic setup. The system combines motion based object segmentation with tracking, and integrates depth information to achieve robust... more
The paper presents a system for automatic video surveillance based on paired cameras in a stereoscopic setup. The system combines motion based object segmentation with tracking, and integrates depth information to achieve robust performance. The methodology encompasses object segmentation based on a class of probabilistic neural networks, shadow removal, computation of a depth map, and object tracking based on an extended set of MPEG-7like feature descriptors including intensity, color, shape, motion and depth. To evaluate the approach, experiments were conducted on a set of outdoor sequences containing both rigid objects and moving persons. The results presented in the paper indicate that the proposed approach is able to achieve accurate segmentation and tracking and handle occlusions efficiently.
... Fig. 4. Sample result frame for the original approach of Viola and Jones. 5 CONCLUSION. ... (2000). 5. Chien, S., Huang, Y., Hsieh, B., Ma, S., Chen, L.: Fast video segmentation algorithm with shadow cancellation, global motion... more
... Fig. 4. Sample result frame for the original approach of Viola and Jones. 5 CONCLUSION. ... (2000). 5. Chien, S., Huang, Y., Hsieh, B., Ma, S., Chen, L.: Fast video segmentation algorithm with shadow cancellation, global motion compensation, and adaptive threshold techniques. ...
An increasing amount of publicly available geo-referenced data enables the identification of patterns of behavior, habits and movements of people. This paper presents results of a case study analysis based on data ser containing publicly... more
An increasing amount of publicly available geo-referenced data enables the identification of patterns of behavior, habits and movements of people. This paper presents results of a case study analysis based on data ser containing publicly available geo-referenced videos downloaded from YouTube, tagged as recorded in Africa. Our goal was to determine major routes of movement across the continent, to determine when people start their trip and the basic means of transportation used. The paper presents results of the analysis conducted on 113.157 unique YouTube records. We were able to identify major travel routes, directions, carriers and even flights favored by people traveling across Africa, information that is potentially valuable to disease outbreak management, airline industry, etc.
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Multispectral remote sensing data are rich source of information for precision agriculture and earth observation that requires advanced methods for its interpretation. In this paper we addressed the problem of crop classification on... more
Multispectral remote sensing data are rich source of information for precision agriculture and earth observation that requires advanced methods for its interpretation. In this paper we addressed the problem of crop classification on multispectral images. The aim is to learn classifier to discriminate between 6 crop types. Different techniques in learning classifiers were employed in order to achieve better accuracy and generalization. We compared obtained results and selected those with potential practical usage. In the light of increasing demand for the extraction of information from remotely collected data, our work contributes to the development of remote sensing inagriculture.
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The paper presents an efficient and reliable approach to automatic people segmentation, tracking and counting, designed for a system with an overhead mounted (zenithal) camera. Upon the initial block-wise background subtraction, k-means... more
The paper presents an efficient and reliable approach to automatic people segmentation, tracking and counting, designed for a system with an overhead mounted (zenithal) camera. Upon the initial block-wise background subtraction, k-means clustering is used to enable the segmentation of single persons in the scene. The number of people in the scene is estimated as the maximal number of clusters
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Video quality as perceived by human observers is the ground truth when Video Quality Assessment (VQA) is in question. It is dependent on many variables, one of them being the content of the video that is being evaluated. Despite the... more
Video quality as perceived by human observers is the ground truth when Video Quality Assessment (VQA) is in question. It is dependent on many variables, one of them being the content of the video that is being evaluated. Despite the evidence that content has an impact on the quality score the sequence receives from human evaluators, currently available VQA databases mostly comprise of sequences which fail to take this into account. In this paper, we aim to identify and analyze differences between human cognitive, affective, and conative responses to a set of videos commonly used for VQA and a set of videos specifically chosen to include video content which might affect the judgment of evaluators when perceived video quality is in question. Our findings indicate that considerable differences exist between the two sets on selected factors, which leads us to conclude that videos starring a different type of content than the currently employed ones might be more appropriate for VQA.
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Visual attention deployment mechanisms allow the Human Visual System to cope with an overwhelming amount of visual data by dedicating most of the processing power to objects of interest. The ability to automatically detect areas of the... more
Visual attention deployment mechanisms allow the Human Visual System to cope with an overwhelming amount of visual data by dedicating most of the processing power to objects of interest. The ability to automatically detect areas of the visual scene that will be attended to by humans is of interest for a large number of applications, from video coding, video quality assessment to scene understanding. Due to this fact, visual saliency (bottom-up attention) models have generated significant scientific interest in recent years. ...
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Design of algorithms that are able to estimate video quality as perceived by human observers is of interest for a number of applications. Depending on the video content, the artifacts introduced by the coding process can be more or less... more
Design of algorithms that are able to estimate video quality as perceived by human observers is of interest for a number of applications. Depending on the video content, the artifacts introduced by the coding process can be more or less pronounced and diversely affect the quality of videos, as estimated by humans. In this paper we propose a new scheme
Research Interests: Computer Science, Video Coding, Neural Networks, Neural Network, Design and Analysis of Algorithms, and 10 moreFeature Selection, Video Streaming, Video Quality, Quality assessment, Video quality assessment, Human Perception, Quality Measures, multi layer perceptron, no reference, and Perceptual Quality
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In this work we propose a novel type of digital video encryption that has several advantages over other currently available digital video encryption schemes. We also present an extended classification of digital video encryption... more
In this work we propose a novel type of digital video encryption that has several advantages over other currently available digital video encryption schemes. We also present an extended classification of digital video encryption algorithms in order to clarify these advantages. We analyze both security and performance aspects of the proposed method, and show that the method is efficient and
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Abstract. This paper proposes a hybrid foreground object detection method suitable for the marine surveillance applications. Our approach combines an existing foreground object detection method with an im-age color segmentation technique... more
Abstract. This paper proposes a hybrid foreground object detection method suitable for the marine surveillance applications. Our approach combines an existing foreground object detection method with an im-age color segmentation technique to improve accuracy. The foreground segmentation method employs a Bayesian decision framework, while the color segmentation part is graph-based and relies on the local variation of edges. We also
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Building an efficient and robust system capable of working in harsh real world conditions represents the ultimate goal of the traffic video surveillance. Despite an evident progress made in the area of statistical background modeling over... more
Building an efficient and robust system capable of working in harsh real world conditions represents the ultimate goal of the traffic video surveillance. Despite an evident progress made in the area of statistical background modeling over the last decade or so, moving object detection is still one of the toughest problems in video surveillance, and new approaches are still emerging. Based on our published method for motion detection in the wavelet domain, we propose a novel, wavelet-based method for robust feature extraction ...
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Abstract. Significant progress has been made in terms of computational models of bottom-up visual attention (saliency). However, efficient ways of comparing these models for still images remain an open research question. The problem is... more
Abstract. Significant progress has been made in terms of computational models of bottom-up visual attention (saliency). However, efficient ways of comparing these models for still images remain an open research question. The problem is even more challenging when dealing with videos and dynamic saliency. The paper proposes a framework for dynamicsaliency model evaluation, based on a new database of diverse videos for which eye-tracking data has been collected. In addition, we present evaluation results obtained ...
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A novel scheme for securing biometric templates of variable size and order is proposed. The proposed scheme is based on a new similarity measure approach, namely the set intersection, which strongly resembles the methodology used in most... more
A novel scheme for securing biometric templates of variable size and order is proposed. The proposed scheme is based on a new similarity measure approach, namely the set intersection, which strongly resembles the methodology used in most of the current state-of-the-art biometrics matching systems. The applicability of the new scheme is compared with that of the existing principal schemes, and it is shown that the new scheme has definite advantages over the existing approaches. The proposed scheme is analyzed both in terms of security and performance.
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Conversational emotion and sentiment analysis approaches rely on Natural Language Understanding (NLU) and audio processing components to achieve the goal of detecting emotions and sentiment based on what is being said. While there has... more
Conversational emotion and sentiment analysis approaches rely on Natural Language Understanding (NLU) and audio processing components to achieve the goal of detecting emotions and sentiment based on what is being said. While there has been marked progress in pushing the state-of-the-art of theses methods on benchmark multimodal data sets, such as the Multimodal EmotionLines Dataset (MELD), the advances still seem to lag behind what has been achieved in the domain of mainstream Automatic Speech Recognition (ASR) and NLU applications and we were unable to identify any widely used products, services or production-ready systems that would enable the user to reliably detect emotions from audio recordings of multi-party conversations. Published, state-of-the-art scientific studies of multi-view emotion recognition seem to take it for granted that a human-generated or edited transcript is available as input to the NLU modules, providing no information of what happens in a realistic application scenario, where audio only is available and the NLU processing has to rely on text generated by ASR. Motivated by this insight, we present a study designed to evaluate the possibility of applying widely-used state-of-the-art commercial ASR products as the initial audio processing component in an emotion-from-speech detection system. We propose an approach which relies on commercially available products and services, such as Google Speech-to-Text, Mozilla DeepSpeech and the NVIDIA NeMo toolkit to process the audio and applies state-of-the-art NLU approaches for emotion recognition, in order to quickly create a robust, production-ready emotion-from-speech detection system applicable to multi-party conversations.
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Large-scale infrastructure, such as China–Europe Railway Express (CER-Express), which connects countries and regions across Asia and Europe, has a potentially profound effect on land use, as evidenced by changes in land cover along the... more
Large-scale infrastructure, such as China–Europe Railway Express (CER-Express), which connects countries and regions across Asia and Europe, has a potentially profound effect on land use, as evidenced by changes in land cover along the railway. To ensure sustainable development of such infrastructure and appropriate land administration, effective ways to monitor and assess its impact need to be developed. Remote sensing based on publicly available satellite imagery represents an obvious choice. In the study presented here, we employ a state-of-the-art deep-learning-based approach to automatically detect different types of land cover based on multispectral Sentinel-2 imagery. We then use these data to conduct and present a study of the changes in land use in two geopolitically diverse regions of interest (in Serbia and China and with and without CER-Express infrastructure) for the period of the last three years. Our results show that the standard image-patch-based land cover classifi...
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In this paper, we present an initial study of possibilities of applying Artificial Intelligence (AI) and computer vision-based approaches aimed to improve and alleviate the process of conducting knowledge assessment over the Microsoft... more
In this paper, we present an initial study of possibilities of applying Artificial Intelligence (AI) and computer vision-based approaches aimed to improve and alleviate the process of conducting knowledge assessment over the Microsoft Teams platform. We did that by developing a deep-neural-network-based system which is able to locate faces and predict emotions based on students’ facial expressions. The system was evaluated on videos recorded during an online assessment of the ability of students to train and deploy deep learning solutions using Python and TensorFlow. We present results of this evaluation and show that, although the accuracy of our algorithm is limited at frame level, as we optimized for computational performance, it provides sufficient information to identify key changes on students’ behavior, which should be brought to the teachers’ attention.
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Color plays an essential role in everyday life and is one of the most important visual cues in human perception. In abstract art, color is one of the essential means to convey the artist's intention and to affect the viewer... more
Color plays an essential role in everyday life and is one of the most important visual cues in human perception. In abstract art, color is one of the essential means to convey the artist's intention and to affect the viewer emotionally. However, colors are rarely experienced in isolation, rather, they are usually presented together with other colors. In fact, the expressive properties of two-color combinations have been extensively studied by artists. It is intriguing to try to understand how color combinations in abstract paintings might affect the viewer emotionally, and to investigate if a computer algorithm can learn this mechanism. In this work, we propose a novel computational approach able to analyze the color combinations in abstract paintings and use this information to infer whether a painting will evoke positive or negative emotions in an observer. We exploit art theory concepts to design our features and the learning algorithm. To make use of the color-group information, we propose inferring the emotions elicited by paintings based on the sparse group lasso approach. Our results show that a relative improvement of between 6% and 8% can be achieved in this way. Finally, as an application, we employ our method to generate Mondrian-like paintings and do a prospective user study to evaluate the ability of our method as an automatic tool for generating abstract paintings able to elicit positive and negative emotional responses in people.
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Research Interests: Cognitive Science, Computer Science, Algorithms, Artificial Intelligence, Computer Vision, and 15 moreImage Processing, Computational Modeling, Medicine, Algorithm, Image Quality, Image coding, Motion compensation, Computer Model, Feature Extraction, Artifacts, Motion, Implementation, Image Enhancement, Information Rate, and Electrical And Electronic Engineering
Research Interests: Computer Science, Algorithms, Computer Graphics, Artificial Intelligence, Colorimetry, and 15 moreMedicine, Image segmentation, Multidisciplinary, Computer Simulation, Lighting, Cluster Analysis, Feedback, Background Subtraction, Background modeling, Information Storage and Retrieval, Image Enhancement, Bayes Theorem, Bayesian Classifier, Artificial Neural Network, and Natural Scenes
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We present the results of an initial study focused on developing a visual AI solution able to recognize individual dogs in unconstrained (wild) images occurring on social media. The work described here is part of joint project done with... more
We present the results of an initial study focused on developing a visual AI solution able to recognize individual dogs in unconstrained (wild) images occurring on social media. The work described here is part of joint project done with Pet2Net, a social network focused on pets and their owners. In order to detect and recognize individual dogs we combine transfer learning and object detection approaches on Inception v3 and SSD Inception v2 architectures respectively and evaluate the proposed pipeline using a new data set containing real data that the users uploaded to Pet2Net platform. We show that it can achieve 94.59% accuracy in identifying individual dogs. Our approach has been designed with simplicity in mind and the goal of easy deployment on all the images uploaded to Pet2Net platform. A purely visual approach to identifying dogs in images, will enhance Pet2Net features aimed at finding lost dogs, as well as form the basis of future work focused on identifying social relation...
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In a weakly-supervised scenario object detectors need to be trained using image-level annotation alone. Since bounding-box-level ground truth is not available, most of the solutions proposed so far are based on an iterative, Multiple... more
In a weakly-supervised scenario object detectors need to be trained using image-level annotation alone. Since bounding-box-level ground truth is not available, most of the solutions proposed so far are based on an iterative, Multiple Instance Learning framework in which the current classifier is used to select the highest-confidence boxes in each image, which are treated as pseudo-ground truth in the next training iteration. However, the errors of an immature classifier can make the process drift, usually introducing many of false positives in the training dataset. To alleviate this problem, we propose in this paper a training protocol based on the self-paced learning paradigm. The main idea is to iteratively select a subset of images and boxes that are the most reliable, and use them for training. While in the past few years similar strategies have been adopted for SVMs and other classifiers, we are the first showing that a self-paced approach can be used with deep-network-based cl...
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The burden of chronic disease and associated disability present a major threat to financial sustainability of healthcare delivery systems. The need for cost-effective early diagnosis and disease prevention is evident driving the... more
The burden of chronic disease and associated disability present a major threat to financial sustainability of healthcare delivery systems. The need for cost-effective early diagnosis and disease prevention is evident driving the development of personalized home health solutions. The proposed solution presents an easy to use ECG monitoring system. The core hardware component is a biosensor dongle with sensing probes at one end, and micro USB interface at the other end, offering reliable and unobtrusive sensing, preprocessing and storage. An additional component is a smart phone, providing both the biosensor's power supply and an intuitive user application for the real-time data reading. The system usage is simplified, with innovative solutions offering plug and play functionality avoiding additional driver installation. Personalized needs could be met with different sensor combinations enabling adequate monitoring in chronic disease, during physical activity and in the rehabilita...
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We conducted an empirical study aimed at identifying and quantifying the relationship between work characteristics, organizational commitment, job satisfaction, job involvement and organizational policies and procedures in the transition... more
We conducted an empirical study aimed at identifying and quantifying the relationship between work characteristics, organizational commitment, job satisfaction, job involvement and organizational policies and procedures in the transition economy of Serbia, South Eastern Europe. The study, which included 566 persons, employed by 8 companies, revealed that existing models of work motivation need to be adapted to fit the empirical data, resulting in a revised research model elaborated in the paper. In the proposed model, job involvement partially mediates the effect of job satisfaction on organizational commitment. Job satisfaction in Serbia is affected by work characteristics but, contrary to many studies conducted in developed economies, organizational policies and procedures do not seem significantly affect employee satisfaction.
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This paper presents the results of a study of the effects of integer (fixed-point) arithmetic implementation on classification accuracy of a popular open-source people detection system based on Histogram of Oriented Gradients. It is... more
This paper presents the results of a study of the effects of integer (fixed-point) arithmetic implementation on classification accuracy of a popular open-source people detection system based on Histogram of Oriented Gradients. It is investigated how the system performance deviates from the reference algorithm performance as integer arithmetic is introduced with different bit-width in several critical parts of the system. In performed experiments, the effects of different bit-width integer arithmetic implementation for four key operations were separately considered: HoG descriptor magnitude calculation, HoG descriptor angle calculation, normalization and SVM classification. It is found that a 13-bit representation of variables is more than sufficient to accurately implement this system in integer arithmetic. The experiments in the paper are conducted for pedestrian detection and the methodology and the lessons learned from this study allow generalization of conclusions to a broader c...
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This chapter presents an overview of the published research focused on the application of visual attention and saliency models to the problem of image and video quality assessment. Determining the perceptual quality of multimedia content... more
This chapter presents an overview of the published research focused on the application of visual attention and saliency models to the problem of image and video quality assessment. Determining the perceptual quality of multimedia content is crucial for achieving quality-of-experience-driven multimedia services. The problem has been gaining significance in the wake of the recent explosion of visual and multimedia applications.Attention and saliency models have the potential to improve the performance of state-of-the-art quality assessment algorithms significantly and are generating increased interest within the research community.