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Search results for: OBJECT DETECTION, BACKGROUND SUBTRACTION
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Performance evaluation of parallel background subtraction on GPU platforms
PublicationImplementation of the background subtraction algorithm on parallel GPUs is presented. The algorithm processes video streams and extracts foreground pixels. The work focuses on optimizing parallel algorithm implementation by taking into account specific features of the GPU architecture, such as memory access, data transfers and work group organization. The algorithm is implemented in both OpenCL and CUDA. Various optimizations of...
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Performance Evaluation of the Parallel Codebook Algorithm for Background Subtraction in Video Stream
PublicationA background subtraction algorithm based on the codebook approach was implemented on a multi-core processor in a parallel form, using the OpenMP system. The aim of the experiments was to evaluate performance of the multithreaded algorithm in processing video streams recorded from monitoring cameras, depending on a number of computer cores used, method of task scheduling, image resolution and degree of image content variability....
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Parallel Background Subtraction in Video Streams Using OpenCL on GPU Platforms
PublicationImplementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access,...
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Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublicationVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
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Layered background modeling for automatic detection of unattended objects in camera images
PublicationAn algorithm for automatic detection of unattended objects in video camera images is presented. First, background subtraction is performed, using an approach based on the codebook method. Results of the detection are then processed by assigning the background pixels to time slots, based on the codeword age. Using this data, moving objects detected during a chosen period may be extracted from the background model. The proposed approach...
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Parallel implementation of background subtraction algorithms for real-time video processing on a supercomputer platform
PublicationResults of evaluation of the background subtraction algorithms implemented on a supercomputer platform in a parallel manner are presented in the paper. The aim of the work is to chose an algorithm, a number of threads and a task scheduling method, that together provide satisfactory accuracy and efficiency of a real-time processing of high resolution camera images, maintaining the cost of resources usage at a reasonable level. Two...
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Detection of moving objects in images combined from video and thermal cameras
PublicationAn algorithm for detection of moving objects in video streams from the monitoring cameras is presented. A system composed of a standard video camera and a thermal camera, mounted in close proximity to each other, is used for object detection. First, a background subtraction is performed in both video streams separately, using the popular Gaussian Mixture Models method. For the next processing stage, the authors propose an algorithm...
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Performance Evaluation of Selected Parallel Object Detection and Tracking Algorithms on an Embedded GPU Platform
PublicationPerformance evaluation of selected complex video processing algorithms, implemented on a parallel, embedded GPU platform Tegra X1, is presented. Three algorithms were chosen for evaluation: a GMM-based object detection algorithm, a particle filter tracking algorithm and an optical flow based algorithm devoted to people counting in a crowd flow. The choice of these algorithms was based on their computational complexity and parallel...
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Detection of vehicles stopping in restricted zones in video from surveillance cameras
PublicationAn algorithm for detection of vehicles that stop in restricted areas, e.g. excluded by traffic rules, is proposed. Classic approaches based on object tracking are inefficient in high traffic scenes because of tracking errors caused by frequent object merging and splitting. The proposed algorithm uses the background subtraction results for detection of moving objects, then pixels belonging to moving objects are tested for stability....
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Moving object detection and tracking for the purpose of multimodal surveillance system in urban areas
PublicationBackground subtraction method based on mixture of Gaussians was employed to detect all regions in a video frame denoting moving objects. Kalman filters were used for establishing relations between the regions and real moving objects in a scene and for tracking them continuously. The objects were represented by rectangles. The objects coupling with adequate regions including the relation of many-to-many was studied experimentally...
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Resolving Conflicts in Object Tracking in Video Stream Employing Key Point Matching
PublicationA novel approach to resolving ambiguous situations in object tracking in video streams is presented. The proposed method combines standard tracking technique employing Kalman filters with global feature matching method. Object detection is performed using a background subtraction algorithm, then Kalman filters are used for object tracking. At the same time, SURF key points are detected only in image sections identified as moving...
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A framework for automatic detection of abandoned luggage in airport terminal
PublicationA framework for automatic detection of events in a video stream transmitted from a monitoring system is presented. The framework is based on the widely used background subtraction and object tracking algorithms. The authors elaborated an algorithm for detection of left and removed objects based on mor-phological processing and edge detection. The event detection algorithm collects and analyzes data of all the moving objects in...
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Camera Orientation-Independent Parking Events Detection
PublicationThe paper describes the method for detecting precise position and time of vehicles parking in a parking lot. This task is trivial in case of favorable camera orientation but gets much more complex when an angle between the camera viewing axis and the ground is small. The method utilizes background subtraction and object tracking algorithms for detecting moving objects in a video stream. Objects are classified into vehicles and...
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Viewpoint independent shape-based object classification for video surveillance
PublicationA method for shape based object classification is presented.Unlike object dimension based methods it does not require any system calibration techniques. A number of 3D object models are utilized as a source of training dataset for a specified camera orientation. Usage of the 3D models allows to perform the dataset creation process semiautomatically. The background subtraction method is used for the purpose of detecting moving objects...
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Performance evaulation of video object tracking algorithm in autonomous surveillance system
PublicationResults of performance evaluation of a video object tracking algorithm are presented. The method of moving objects detection and tracking is based on background modelling with mixtures of Gaussians and Kalman filters. An emphasis is put on algorithm's efficiency with regards to its settings. Utilized methods of performance evaluation based on comparison of algorithm output to manually prepared reference data are introduced. The...
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Performance evaluation of video object tracking algorithm in autonomous surveillance system
PublicationResults of performance evaluation of a video object tracking algorithm are presented. The method of moving objects detection and tracking is based on background modelling with mixtures of Gaussians and Kalman filters. An emphasis is put on algorithm's efficiency with regards to its settings. Utilized methods of performance evaluation based on comparison of algorithm output to manually prepared reference data are introduced. The...
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Using Disparity Map for Moving Object Position Estimation in Pan Tilt Camera Images
PublicationIn this paper we present the algorithm for rapid moving object position estimation in an images acquired from pan tilt camera. Detection of a moving object in a image acquired from a moving camera might be quite challenging. Standard methods that relay on analyzing two consecutive frames are not applicable due to the changing background. To overtake this problem we decided to evaluate the possibility of calculating a disparity...
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Aktywny system RFID do lokalizacji i identyfikacji obiektów w wielomodalnej infrastrukturze bezpieczeństwa
PublicationPrzedstawiono prace koncepcyjne, badawcze oraz implementacyjne skoncentrowane na praktycznej realizacji systemu detekcji obiektów z wykorzystaniem kamer wizyjnych i identyfikacji radiowej. Zaproponowano rozbudowę wielomodalnego teleinformatycznego systemu bezpieczeństwa o warstwę identyfikacji radiowej obiektów. Omówiono założenia zaprojektowanego systemu oraz opracowaną warstwę sprzętową. Zaproponowano i przedyskutowano praktyczne...
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Video content analysis in the urban area telemonitoring system
PublicationThe task of constant monitoring of video streams from a large number of cameras and reviewing the recordings in order to find a specified event requires a considerable amount of time and effort from the system operators and it is prone to errors. A solution to this problem is an automatic system for constant analysis of camera images being able to raise an alarm if a predefined event is detected. The chapter presents various aspects...
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Visual Object Tracking System Employing Fixed and PTZ Cameras
PublicationThe paper presents a video monitoring system utilizing fixed and PTZ cameras for tracking of moving objects. First type of camera provides image for background modelling, being employed for foreground objects localization. Estimated objects locations are then utilised for steering of PTZ cameras when observing targeted objects with high close-ups. Objects are classified into several classes, then basic event detection is being...
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Sensorless Fault Detection of Induction Motor with Inverter Output Filter
PublicationThe paper presents the problem of monitoring and fault detection of a sensorless voltage inverter fed squirrel cage induction motor with LC filter. The detection is based on load torque estimation of the investigated torque transmission system. The load torque is calculated besides the computation of other variables that are mandatory for sensorless drive operation such as rotor flux and speed. The implemented LC filter smooths...
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System for tracking multiple trains on a test railway track
PublicationSeveral problems may arise when multiple trains are to be tracked using two IP camera streams. In this work, real-life conditions are simulated using a railway track model based on the Pomeranian Metropolitan Railway (PKM). Application of automatic clustering of optical flow is investigated. A complete tracking solution is developed using background subtraction, blob analysis, Kalman filtering, and a Hungarian algorithm. In total,...
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System for tracking multiple trains on a test railway track
PublicationSeveral problems may arise when multiple trains are to be tracked using two IP camera streams. In this work, real-life conditions are simulated using a railway track model based on the Pomeranian Metropolitan Railway (PKM). Application of automatic clustering of optical flow is investigated. A complete tracking solution is developed using background subtraction, blob analysis, Kalman filtering, and a Hungarian algorithm. In total,...
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Multi-core processing system for real-time image processing in embedded computer vision applications
PublicationW artykule opisano architekturę wielordzeniowego programowalnego systemu do przetwarzania obrazów w czasie rzeczywistym. Dane obrazu są przetwarzane równocześnie przez wszystkie procesory. System umożliwia niskopoziomowe przetwarzanie obrazów,np. odejmowanie tła, wykrywanie obiektów ruchomych, transformacje geometryczne, indeksowanie wykrytych obiektów, ocena ich kształtu oraz podstawowa analiza trajektorii ruchu. Ang:This paper...
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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublicationObject detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detection to achieve higher performance. However, existing models have some limitations such as overfitting problem and lower efficiency in small object detection. Object detection in remote...
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Audio content analysis in the urban area telemonitoring system
PublicationArtykuł przedstawia możliwości rozwinięcie monitoringu miejskiego o automatyczną analizę dźwięku. Przedstawiono metody parametryzacji dźwięku, które możliwe są do zastosowania w takim systemie oraz omówiono aspekty techniczne implementacji. W kolejnej części przedstawiono system decyzyjny oparty na drzewach zastosowany w systemie. System ten rozpoznaje dźwięki niebezpieczne (strzał, rozbita szyba, krzyk) wśród dźwięków zarejestrowanych...
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Multiple Cues-Based Robust Visual Object Tracking Method
PublicationVisual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Hardware-Software Implementation of a Sensor Network for CityTraffic Monitoring Using the FPGA- and ASIC-Based Sensor Nodes
PublicationArtykuł opisuje prototypową sieć sensorową do monitorowania ruchu pojazdów w mieście. Węzły sieci sensorowej, wyposażone w kamerę o niskiej rozdzielczości, obserwują ulice i wykrywają poruszające się obiekty. Detekcja obiektów jest realizowana w oparciu o własny algorytm segmentacji obrazów, wykorzystujący podwójne odejmowanie tła, wykrywanie krawędzi i cieni, działający na dedykowanym systemie mikroelektronicznym typu ''System...
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Learning sperm cells part segmentation with class-specific data augmentation
PublicationInfertility affects around 15% of couples worldwide. Male fertility problems include poor sperm quality and low sperm count. The advanced fertility treatment methods like ICSI are nowadays supported by vision systems to assist embryologists in selecting good quality sperm. Computer-Assisted Semen Analysis (CASA) provides quantitative and qualitative sperm analysis concerning concentration, motility, morphology, vitality, and fragmentation....
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Risk Diagnosis and Management with BBN for Civil Engineering Projects during Construction and Operation
PublicationThe authors demonstrate how expert knowledge about the construction and operation phases combined with monitoring data can be utilized for the diagnosis and management of risks typical to large civil engineering projects. The methodology chosen for estimating the probabilities of risk elements is known as Bayesian Belief Networks (BBN). Using a BBN model one can keep on updating the risk event probabilities as the new evidence...
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Robustness in Compressed Neural Networks for Object Detection
PublicationModel compression techniques allow to significantly reduce the computational cost associated with data processing by deep neural networks with only a minor decrease in average accuracy. Simultaneously, reducing the model size may have a large effect on noisy cases or objects belonging to less frequent classes. It is a crucial problem from the perspective of the models' safety, especially for object detection in the autonomous driving...
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CMGNet: Context-aware middle-layer guidance network for salient object detection
PublicationSalient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects in an image. To address the challenges of gridding issues and feature...
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Fuzzy Sets in the GIS Environment in the Location of Objects on the Surface of Water Bodies
PublicationThe issue presented here focuses on concerns about the localization of the object on water surface. The article shows how to facilitate localization process by applying mathematical solutions characterized by simplicity, rapid action and delivering credible results. The paper shows the results of background experiments, which enabled to collect technical parameters needed for conducting simulation testing. The research has been...
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Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection
PublicationRemote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...
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Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations
PublicationEvaluation of sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for discerning between the events being in focus and the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the...
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MULTI-CRITERIA MODEL IN MULTIFUNCTIONAL BUILDING SYSTEM DESIGN PROCESS
PublicationThe paper presents a multi-criteria approach in multifunctional building system design process. The aim is to develop a theory relative to the engineering system of multifunctional with a mathematical representation defined by a holistic network for the lifecycle of the designed object. The idea of work was to define the structure of a complex system. Background for the presented field is to develop a design strategy for multifunctional...
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Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations
PublicationAn evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublicationRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublicationRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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The circle object detection with the use of Msplit estimation
PublicationThe paper presents the use of Msplit(q) - estimation in the filtration and aggregation of point clouds containing a known number of elliptical shapes with preliminary unknown - locations and dimensions. These theoretical solutions may have practical relevance especially in the modelling of terrestrial laser scanning data of objects that have similar shape to circles. Mentioned shapes can be scanned of tree trunks, columns, gutters,...
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Point-pixel fusion for object detection and depth estimation
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Multiscaled Hybrid Features Generation for AdaBoost Object Detection
PublicationThis work presents the multiscaled version of modified census features in graphical objects detection with AdaBoost cascade training algorithm. Several experiments with face detector training process demonstrate better performance of such features over ordinal census and Haar-like approaches. The possibilities to join multiscaled census and Haar features in single hybrid cascade of strong classifiers are also elaborated and tested....
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Resolving conflicts in object tracking for automatic detection of events in video
PublicationW referacie przedstawiono algorytm rozwiązywania konfliktów w śledzeniu obiektów ruchomych. Proponowana metoda wykorzystuje predykcję stanu obiektu obliczaną przez filtry Kalmana oraz dopasowuje wykryte obiekty do struktur śledzących ich ruch na podstawie deskryptorów koloru i tekstury. Omówiono specyficzne sytuacje powodujące konflikty, takie jak rozdzielanie obiektów. Przedstawiono wyniki testów. Algorytm może być zastosowany...
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Resolving conflicts in object tracking for automatic detection of events in video
PublicationAn algorithm for resolving conflicts in tracking of moving objects is presented. The proposed approach utilizes predicted states calculated by Kalman filters for estimation of trackers position, then it uses color and texture descriptors in order to match moving objects with trackers. Problematic situations, such as splitting objects, are addressed. Test results are presented and discussed. The algorithm may be used in the system...
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Modular machine learning system for training object detection algorithms on a supercomputer
PublicationW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
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Object-oriented approach to oil spill detection using ENVISAT ASAR images
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An object-based SAR image iceberg detection algorithm applied to the Amundsen Sea
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City as a product. Architecture as an Economic Instrument. Are Global Cities People-Friendly Places?
PublicationWhile spending time in our everyday urban environment do we ever think how particular architecture influences the economic value of that space? Space has its measurable financial value. From the economic point of view a place can be treated as a product that fights for appearing in tourists’ and investors’ consciousnesses. Space - treated as an object of demand and supply - becomes an element in a marketing game. To reach its...
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Exploring the impact of cultural context on eye-tracking studies of architectural monuments in selected European cities: Sustainable heritage management.
PublicationSustainable management of architectural heritage requires conducting an inclusive diagnosis of users’ opinions, considering both residents and tourists as the recipients of urban space. Given the cultural diversity within these groups, proposing the use of eye-trackers (ET) as an alternative to traditional public consultation prompts the need to assess the method’s advantages and disadvantages. It remains uncertain whether individuals...