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Journal articles on the topic 'OpenNI'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Tang, Chen, and Zhong Hua Hu. "Basketball Detection Based on Moving Robot." Applied Mechanics and Materials 734 (February 2015): 629–32. http://dx.doi.org/10.4028/www.scientific.net/amm.734.629.

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The purpose of this study is to introduce a method based on color space and object shape, in order to get data of ball by openni and to obtain a coordinate of the point. The distance from robot to basketball with respect to basketball position was achieved. Our results shows that the method has strong stability and real-time performance to use in robots.

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Adachi, Takayuki, Masafumi Goseki, Hiroshi Takemura, Hiroshi Mizoguchi, Fusako Kusunoki, Masanori Sugimoto, Etsuji Yamaguchi, Shigenori Inagaki, and Yoshiaki Takeda. "Integration of Ultrasonic Sensors and Kinect Sensors for People Distinction and 3D Localization." Journal of Robotics and Mechatronics 25, no. 4 (August 20, 2013): 762–66. http://dx.doi.org/10.20965/jrm.2013.p0762.

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The method proposed here for 3D position measurement and identification of individuals by integrating ultrasonic and Kinect sensors uses ultrasonic transmitter tags with unique identifiers. Ultrasonic sensors measure the 3D positions of and identify tagged individuals, but cannot make measurements if there are no receivers in the direction of ultrasonic waves from transmitters. Kinect sensors measure 3D positions of individuals and track them with OpenNI, but Kinect sensors cannot make measurements if occlusion occurs due to the overlapping of individuals. Evaluation results show that the method proposed here is more robust than methods only using either ultrasonic or Kinect sensors.

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Liu, Tsun Te, Ching Tang Hsieh, Ruei Chi Chung, and Yuan Sheng Wang. "Physical Rehabilitation Assistant System Based on Kinect." Applied Mechanics and Materials 284-287 (January 2013): 1686–90. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.1686.

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In this paper, we present a physical rehabilitation assistant system based on skeleton detection with Kinect. The users do not have to install the detectors on the exercise equipment anymore. And then, they can just use the rehabilitation equipment with Kinect using the skeleton detection technique. In this study, we build a normalized three-dimensional Cartesian coordinates location of correct postures under OpenNI system. We find out 15 human skeleton joints with three dimensional coordinates and calculate the feature values, than we use support vector machine (SVM) as classifier to define the accuracy of posture. Finally, the system can judge the correct degree of user’s postures. Also, we can have the rehabilitation purpose.

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Kim, Hyesuk, and Incheol Kim. "Human Activity Recognition as Time-Series Analysis." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/676090.

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We propose a system that can recognize daily human activities with a Kinect-style depth camera. Our system utilizes a set of view-invariant features and the hidden state conditional random field (HCRF) model to recognize human activities from the 3D body pose stream provided by MS Kinect API or OpenNI. Many high-level daily activities can be regarded as having a hierarchical structure where multiple subactivities are performed sequentially or iteratively. In order to model effectively these high-level daily activities, we utilized a multiclass HCRF model, which is a kind of probabilistic graphical models. In addition, in order to get view-invariant, but more informative features, we extract joint angles from the subject’s skeleton model and then perform the feature transformation to obtain three different types of features regarding motion, structure, and hand positions. Through various experiments using two different datasets, KAD-30 and CAD-60, the high performance of our system is verified.

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Hastomo, Widi. "GESTURE RECOGNITION FOR PENCAK SILAT TAPAK SUCI REAL-TIME ANIMATION." Jurnal Ilmu Komputer dan Informasi 13, no. 2 (July 1, 2020): 77–87. http://dx.doi.org/10.21609/jiki.v13i2.855.

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The main target in this research is a design of a virtual martial arts training system in real-time and as a tool in learning martial arts independently using genetic algorithm methods and dynamic time warping. In this paper, it is still in the initial stages, which is focused on taking data sets of martial arts warriors using 3D animation and the Kinect sensor cameras, there are 2 warriors x 8 moves x 596 cases/gesture = 9,536 cases. Gesture Recognition Studies are usually distinguished: body gesture and hand and arm gesture, head and face gesture, and, all three can be studied simultaneously in martial arts pencak silat, using martial arts stance detection with scoring methods. Silat movement data is recorded in the form of oni files using the OpenNI ™ (OFW) framework and BVH (Bio Vision Hierarchical) files as well as plug-in support software on Mocap devices. Responsiveness is a measure of time responding to interruptions, and is critical because the system must be able to meet the demand.

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Heickal, Hasnain, Tao Zhang, and Md Hasanuzzaman. "Computer Vision-Based Real-Time 3D Gesture Recognition Using Depth Image." International Journal of Image and Graphics 15, no. 01 (January 2015): 1550004. http://dx.doi.org/10.1142/s0219467815500047.

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Gesture is one of the fundamental ways of human machine natural interaction. To understand gesture, the system should be able to interpret 3D movements of human. This paper presents a computer vision-based real-time 3D gesture recognition system using depth image which tracks 3D joint position of head, neck, shoulder, arms, hands and legs. This tracking is done by Kinect motion sensor with OpenNI API and 3D motion gesture is recognized using the movement trajectory of those joints. User to Kinect sensor distance is adapted using proposed center of gravity (COG) correction method and 3D joint position is normalized using proposed joint position normalization method. For gesture learning and recognition, data mining classification algorithms such as Naive Bayes and neural network is used. The system is trained to recognize 12 gestures used by umpires in a cricket match. It is trained and tested using about 2000 training instances for 12 gesture of 15 persons. The system is tested using 5-fold cross validation method and achieved 98.11% accuracy with neural network and 88.84% accuracy with Naive Bayes classification method.

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Hsieh, Cheng Tiao. "A New Kinect-Based Scanning System and its Application." Applied Mechanics and Materials 764-765 (May 2015): 1375–79. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.1375.

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This paper aims at presenting a simple approach utilizing a Kinect-based scanner to create models available for 3D printing or other digital manufacturing machines. The outputs of Kinect-based scanners are a depth map and they usually need complicated computational processes to prepare them ready for a digital fabrication. The necessary processes include noise filtering, point cloud alignment and surface reconstruction. Each process may require several functions and algorithms to accomplish these specific tasks. For instance, the Iterative Closest Point (ICP) is frequently used in a 3D registration and the bilateral filter is often used in a noise point filtering process. This paper attempts to develop a simple Kinect-based scanner and its specific modeling approach without involving the above complicated processes.The developed scanner consists of an ASUS’s Xtion Pro and rotation table. A set of organized point cloud can be generated by the scanner. Those organized point clouds can be aligned precisely by a simple transformation matrix instead of the ICP. The surface quality of raw point clouds captured by Kinect are usually rough. For this drawback, this paper introduces a solution to obtain a smooth surface model. Inaddition, those processes have been efficiently developed by free open libraries, VTK, Point Cloud Library and OpenNI.

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Pham, Huy-Hieu, Thi-Lan Le, and Nicolas Vuillerme. "Real-Time Obstacle Detection System in Indoor Environment for the Visually Impaired Using Microsoft Kinect Sensor." Journal of Sensors 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/3754918.

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Any mobility aid for the visually impaired people should be able to accurately detect and warn about nearly obstacles. In this paper, we present a method for support system to detect obstacle in indoor environment based on Kinect sensor and 3D-image processing. Color-Depth data of the scene in front of the user is collected using the Kinect with the support of the standard framework for 3D sensing OpenNI and processed by PCL library to extract accurate 3D information of the obstacles. The experiments have been performed with the dataset in multiple indoor scenarios and in different lighting conditions. Results showed that our system is able to accurately detect the four types of obstacle: walls, doors, stairs, and a residual class that covers loose obstacles on the floor. Precisely, walls and loose obstacles on the floor are detected in practically all cases, whereas doors are detected in 90.69% out of 43 positive image samples. For the step detection, we have correctly detected the upstairs in 97.33% out of 75 positive images while the correct rate of downstairs detection is lower with 89.47% from 38 positive images. Our method further allows the computation of the distance between the user and the obstacles.

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Gember-Jacobson, Aaron, Raajay Viswanathan, Chaithan Prakash, Robert Grandl, Junaid Khalid, Sourav Das, and Aditya Akella. "OpenNF." ACM SIGCOMM Computer Communication Review 44, no. 4 (February 25, 2015): 163–74. http://dx.doi.org/10.1145/2740070.2626313.

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Ridler, Marc E., Nils van Velzen, Stef Hummel, Inge Sandholt, Anne Katrine Falk, Arnold Heemink, and Henrik Madsen. "Data assimilation framework: Linking an open data assimilation library (OpenDA) to a widely adopted model interface (OpenMI)." Environmental Modelling & Software 57 (July 2014): 76–89. http://dx.doi.org/10.1016/j.envsoft.2014.02.008.

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Ma, Yunzhi, and Luc Beaulieu. "Abstract ID: 184 OpenDNA: An OpenCL-based GPU Monte Carlo simulation code for microdosimetry." Physica Medica 42 (October 2017): 39–40. http://dx.doi.org/10.1016/j.ejmp.2017.09.096.

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Gregersen, J. B., P. J. A. Gijsbers, and S. J. P. Westen. "OpenMI: Open modelling interface." Journal of Hydroinformatics 9, no. 3 (July 1, 2007): 175–91. http://dx.doi.org/10.2166/hydro.2007.023.

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Management issues in many sectors of society demand integrated analysis that can be supported by integrated modelling. Since all-inclusive modelling software is difficult to achieve, and possibly even undesirable, integrated modelling requires the linkage of individual models or model components that address specific domains. Emerging from the water sector, the OpenMI has been developed with the purpose of being the glue that can link together model components from various origins. The OpenMI provides a standardized interface to define, describe and transfer data on a time basis between software components that run simultaneously, thus supporting systems where feedback between the modelled processes is necessary in order to achieve physically sound results. The OpenMI allows the linking of models with different spatial and temporal representations: for example, linking river models and groundwater models, where the river model typically uses a one-dimensional grid and a short timestep and the groundwater model uses a two- or three-dimensional grid and a longer timestep. The OpenMI is designed to accommodate the easy migration of existing modelling systems, since their re-implementation may not be economically feasible due to the large investments that have been put into the development and testing of these systems.

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Bhattacharyya, Shuvra S., Gordon Brebner, Jörn W. Janneck, Johan Eker, Carl von Platen, Marco Mattavelli, and Mickaël Raulet. "OpenDF." ACM SIGARCH Computer Architecture News 36, no. 5 (December 20, 2008): 29–35. http://dx.doi.org/10.1145/1556444.1556449.

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Sand, Urban, Stephan Balmer, Luca Obertüfer, and Emre Sarigol. "OPENKI The platform for open education." Aarhus Series on Human Centered Computing 1, no. 1 (October 5, 2015): 2. http://dx.doi.org/10.7146/aahcc.v1i1.21319.

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<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>In this demo we aim to introduce and demonstrate O</span><span>PENKI</span><span>, an interactive web-platform designed and developed with the aim of facilitating a barrier-free access to education. In a nutshell, O</span><span>PENKI </span><span>is an open-source tool to facilitate self- organized, regionalized and offline knowledge exchange. It provides a basis for mediating non-commercial education op- portunities by means of acting as a meeting point for indi- viduals interested in similar subjects. The platform connects individuals who are interested learning or teaching specific topics, or have a physical space to offer where the coordi- nated events can take place, and gather themselves around interest groups. Through its lightweight interface, all stages of a learning processes are made possible from the selection of topics and the organization and execution of courses up to the documentation of the learning material. </span></p></div></div></div>

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Роганов, Владимир Александрович, Валерий Иванович Осипов, and Герман Анатольевич Матвеев. "Integration of Mantevo MiniAMR and OpenTS . Comparison of OpenTS DMPI and Open MPI." Program Systems: Theory and Applications 9, no. 4 (December 17, 2018): 361–81. http://dx.doi.org/10.25209/2079-3316-2018-9-4-361-381.

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Mantevo MiniAMR – инструментальное средство для распараллеливания широкого класса 3D приложений с использованием адаптивной расчетной сетки. Оно может быть применено для параллельной реализации разностных схем; систем, которые моделируются с помощью уравнений с частными производными. Проведена интеграция пакета MiniAMR и системы для параллельного программирования OpenTS. Произведено сравнение OpenTS DMPI и Open MPI.

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Utke, Jean, Uwe Naumann, Mike Fagan, Nathan Tallent, Michelle Strout, Patrick Heimbach, Chris Hill, and Carl Wunsch. "OpenAD/F." ACM Transactions on Mathematical Software 34, no. 4 (July 15, 2008): 1–36. http://dx.doi.org/10.1145/1377596.1377598.

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Scacchi, Walt. "OpenEC/B." ACM SIGSOFT Software Engineering Notes 30, no. 4 (July 2005): 1–5. http://dx.doi.org/10.1145/1082983.1083270.

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Harpham, Quillon, Paul Cleverley, and David Kelly. "The FluidEarth 2 implementation of OpenMI 2.0." Journal of Hydroinformatics 16, no. 4 (December 16, 2013): 890–906. http://dx.doi.org/10.2166/hydro.2013.190.

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Following the release of the OpenMI 2.0 standard for model coupling with reference object classes (interfaces) in C# and Java, a set of tools including a Software Development Kit (SDK) and Graphical User Interface (GUI) is expected to accompany it. These are necessary to enable numerical model developers to easily adapt their models to become OpenMI compliant and to allow modellers to easily assemble and run compositions of them. FluidEarth 2 is an HR Wallingford initiative providing these open source tools for the .net 4.0 Framework together with training, community support and sample models. They are the only such open source tools available so in this sense they act as the reference SDK and GUI for OpenMI 2.0 with .net. The purpose of this paper is to outline these and demonstrate a set of examples. A series of components were successfully constructed and compositions built. These include training models designed to demonstrate different aspects of model coupling, moving to industry strength model codes simulating dam-break bathymetry updates. The FluidEarth 2 tools have been designed to be cross-platform and have been tested under Windows and Linux (using Mono). Usage is successfully demonstrated, providing an environment for integrated modelling with OpenMI 2.0.

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Puttapirat, Pargorn, Haichuan Zhang, Jingyi Deng, Yuxin Dong, Jiangbo Shi, Peiliang Lou, Chunbao Wang, Lixia Yao, Xiangrong Zhang, and Chen Li. "OpenHI: open platform for histopathological image annotation." International Journal of Data Mining and Bioinformatics 22, no. 4 (2019): 328. http://dx.doi.org/10.1504/ijdmb.2019.101393.

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Krischmann, T., H. Urban, and C. Schranz. "Entwicklung eines openBIM-Bewilligungsverfahrens/Development of an openBIM submission process." Bauingenieur 95, no. 09 (2020): 335–44. http://dx.doi.org/10.37544/0005-6650-2020-09-61.

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Zusammenfassung Das BIM-Modell als zentrale Stelle der Daten und Informationen weist vielfältige Potenziale für den gesamten Lebenszyklus eines Bauwerks auf. Noch weitgehend ungenutzt sind diese Vorteile im Baubewilligungsverfahren. Die Stadt Wien betritt einen sehr innovativen Weg und startete das von der EU geförderte Forschungsprojekt BRISE-Vienna, in dem ein komplettes openBIM-Bewilligungsverfahren entwickelt wird. Dieser Artikel befasst sich mit den dafür notwendigen openBIM-Grundlagen, den Prüfroutinen sowie der rechtlichen Situation in Wien. Sie dienen als Basis für die Definition unterschiedlicher BIM-basierter Modelle, die im Zuge des Baubewilligungsverfahrens erforderlich sind. Neben dem von den Planenden eingereichtem Bauantragsmodell entstehen aus baurechtlichen Anforderungen ein Referenzmodell und ein Antragsinformationsmodell. Die letzteren Modelle dienen der teilautomatischen baurechtlichen Überprüfung des Bauantragsmodells. Für die Modellprüfung ist die Entwicklung eines detaillierten Prüfsettings erforderlich. Dies ist ein iterativer Entwicklungsprozess, der im Anschluss an das Forschungsprojekt schrittweise in den Realbetrieb eines openBIM-Bewilligungsverfahrens übergehen soll.

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Figueiredo, Marco Antonio C., Edans F. Oliveira Sandes, Genaina N. Rodrigues, George L. M. Teodoro, and Alba Cristina M. A. Melo. "MASA‐OpenCL: Parallel pruned comparison of long DNA sequences with OpenCL." Concurrency and Computation: Practice and Experience 31, no. 11 (October 21, 2018): e5039. http://dx.doi.org/10.1002/cpe.5039.

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Domínguez, César, Jónathan Heras, and Vico Pascual. "IJ-OpenCV: Combining ImageJ and OpenCV for processing images in biomedicine." Computers in Biology and Medicine 84 (May 2017): 189–94. http://dx.doi.org/10.1016/j.compbiomed.2017.03.027.

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Wang, Jian Ping, Jian Chen, and Chun Hong Li. "Research for Hydrological Modelling System Technology Based on OpenMI." Advanced Materials Research 347-353 (October 2011): 1806–15. http://dx.doi.org/10.4028/www.scientific.net/amr.347-353.1806.

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There has been a variety wide of hydrological simulation models, each model has its own characteristics. Hydrological modelling considers more and more detailed physical mechanism. And involved professional models also increased great significantly. Therefore, it is particularly important to establish an open unified model interface standards to make a data communication among different models and quickly formulate modelling systems suitable for the characteristics of target watershed. OpenMI emerged at the right moment to satisfy the requirements of above situations. The thesis bases on OpenMI to design hydrological modelling systems and inherits OpenMI framework of design, request/feedback mechanism and hierarchy facing to modules. This design can solve the assembly link problem of cross-language and multi-type models and make a beneficial attempt for hydrological modelling system efficient integration.

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Blind, M., and J. B. Gregersen. "Towards an Open Modelling Interface (OpenMI) the HarmonIT project." Advances in Geosciences 4 (August 9, 2005): 69–74. http://dx.doi.org/10.5194/adgeo-4-69-2005.

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Abstract. The Water Framework Directive (WFD) poses an immense challenge to water management in Europe. Aiming at a "good ecological status" of surface waters in 2015, integrated river basin management plans need to be in place by 2009, and broadly supported by stakeholders. Information & Communication Technology (ICT) tools, such as computational models, are very helpful in designing river basin management plans (rbmp-s). However, many scientists believe that a single integrated modelling system to support the WFD cannot be developed, and integrated systems need to be quite tailored to the local situation and evolve during a collaborative planning process. As a consequence there is an urgent need to increase the flexibility of modelling systems, such that dedicated model systems can be developed from available building blocks. In the recent past a number of initiatives have been started to develop an IT framework for modelling to meet the required flexibility. In Europe the international project HarmonIT, which is sponsored by the European Commission, is developing and implementing a standard interface for modelling components and other relevant tools: The Open Modelling Interface (OpenMI). This paper describes the HarmonIT project and objectives in general. The current progress is described. It describes the roles for different types of stakeholders in modelling, varying from software coders to non-specialized users of decision support systems. It will provide insight in the requirements imposed when using the OpenMI.

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Knapen, Rob, Sander Janssen, Onno Roosenschoon, Peter Verweij, Wim de Winter, Michel Uiterwijk, and Jan-Erik Wien. "Evaluating OpenMI as a model integration platform across disciplines." Environmental Modelling & Software 39 (January 2013): 274–82. http://dx.doi.org/10.1016/j.envsoft.2012.06.011.

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Lee, Jieh-Sheng, and Jieh Hsiang. "Patent claim generation by fine-tuning OpenAI GPT-2." World Patent Information 62 (September 2020): 101983. http://dx.doi.org/10.1016/j.wpi.2020.101983.

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Jakob, Robert, and Dieter J. Vonderschmitt. "Development of a user-oriented completely openin vitrodiagnostics system." Journal of Automatic Chemistry 18, no. 1 (1996): 1–5. http://dx.doi.org/10.1155/s1463924696000016.

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Liu, Haiyan, Xiaomin Liu, and Zhenhua Xu. "Research on model component method based on OpenMI technology." E3S Web of Conferences 260 (2021): 03005. http://dx.doi.org/10.1051/e3sconf/202126003005.

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Open Model Interface (OpenMI) technology can construct standardized components with unified timing interface and standardized data interaction. This provides a standardized method for integrating multiple models with different interfaces and functions. This paper briefly introduces the operation principle of OpenMI technology and the process of model standardization, and describes the seven key steps of model transplantation by taking the one-dimensional hydraulic model of the Yellow River as an example.

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Guilherme, M. Pereira, Albertazzi G. Jr Armando, and E. M. Haertel Maryah. "Kamera kalibráció OpenCV használatával." Fiatal Műszakiak Tudományos Ülésszaka 1. (2014) (2014): 329–32. http://dx.doi.org/10.36243/fmtu-2014.075.

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Jansen, Rhijja, and Adri Van Beelen. "Opeens heb je het…" TvV Tijdschrift voor Verzorgenden 50, no. 3 (February 22, 2018): 30–33. http://dx.doi.org/10.1007/s41193-018-0026-0.

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Stolarski, Kamil. "OpenBIM kompatybilny z prawem." MATERIAŁY BUDOWLANE 1, no. 3 (March 5, 2018): 86–87. http://dx.doi.org/10.15199/33.2018.03.34.

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Dunk, Stijn. "Opeens wordt technologie omarmd." Advocatenblad 100, no. 3 (March 2020): 16–17. http://dx.doi.org/10.5553/ab/0165-13312020100003006.

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Zapart, Christopher A. "OpenCL Implementation of NeuroIsing." Progress of Theoretical Physics Supplement 194 (2012): 28–42. http://dx.doi.org/10.1143/ptps.194.28.

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Yamamoto, Yuka. "Combining LabVIEW with OpenCV." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2018 (2018): 2P2—D03. http://dx.doi.org/10.1299/jsmermd.2018.2p2-d03.

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Becker, Bernhard P., and Holger Schüttrumpf. "An OpenMI module for the groundwater flow simulation programme Feflow." Journal of Hydroinformatics 13, no. 1 (March 19, 2010): 1–12. http://dx.doi.org/10.2166/hydro.2010.039.

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The OpenMI standard defines an interface that allows time-dependent models to exchange data at runtime. The migration of a flow simulation programme to OpenMI compliance usually requires changes in the source code or even a reorganisation of the programme sequence. Users of commercial flow simulation programmes depend on the software producer if they want to couple their models according to the OpenMI standard. We describe how we made the groundwater flow simulation programme Feflow OpenMI compliant without changing the source code: an OpenMI-compliant control application communicates with Feflow via remote procedure calls. A basic prerequisite for applying this method is an entry point into the flow simulation programme that allows to modify the model data during runtime and to implement the remote procedure calls. Feflow meets this requirement as it provides the interface manager (IFM). The mode of operation is explained with a simple test case including an inundation model and a Feflow groundwater model.

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Gregersen, J. B., P. J. A. Gijsbers, S. J. P. Westen, and M. Blind. "OpenMI: the essential concepts and their implications for legacy software." Advances in Geosciences 4 (August 9, 2005): 37–44. http://dx.doi.org/10.5194/adgeo-4-37-2005.

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Abstract. Information & Communication Technology (ICT) tools such as computational models are very helpful in designing river basin management plans (rbmp-s). However, in the scientific world there is consensus that a single integrated modelling system to support e.g. the implementation of the Water Framework Directive cannot be developed and that integrated systems need to be very much tailored to the local situation. As a consequence there is an urgent need to increase the flexibility of modelling systems, such that dedicated model systems can be developed from available building blocks. The HarmonIT project aims at precisely that. Its objective is to develop and implement a standard interface for modelling components and other relevant tools: The Open Modelling Interface (OpenMI) standard. The OpenMI standard has been completed and documented. It relies entirely on the "pull" principle, where data are pulled by one model from the previous model in the chain. This paper gives an overview of the OpenMI standard, explains the foremost concepts and the rational behind it.

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Reußner, F., J. Alex, M. Bach, M. Schütze, and D. Muschalla. "Basin-wide integrated modelling via OpenMI considering multiple urban catchments." Water Science and Technology 60, no. 5 (May 1, 2009): 1241–48. http://dx.doi.org/10.2166/wst.2009.471.

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Integrated modelling is currently receiving a lot of attention in the field of urban hydrology. This paper describes a method for carrying out integrated modelling of sewer systems and rivers, where the constituent models are linked to each other using the European OpenMI interface. This has the advantage that, once the necessary software extensions have been carried out, the data sets describing the subsystems can be used as they are without any need for adaptation.

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Harpham, Q. K., A. Hughes, and R. V. Moore. "Introductory overview: The OpenMI 2.0 standard for integrating numerical models." Environmental Modelling & Software 122 (December 2019): 104549. http://dx.doi.org/10.1016/j.envsoft.2019.104549.

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Bulatewicz, T., A. Allen, J. M. Peterson, S. Staggenborg, S. M. Welch, and D. R. Steward. "The Simple Script Wrapper for OpenMI: Enabling interdisciplinary modeling studies." Environmental Modelling & Software 39 (January 2013): 283–94. http://dx.doi.org/10.1016/j.envsoft.2012.07.006.

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JETENSKÝ, Pavel. "USING OPEN SOURCE OPENCV LIBRARY FOR PRACTICAL COURSES OF COMPUTER VISION." Journal of Technology and Information 5, no. 1 (April 1, 2013): 115–19. http://dx.doi.org/10.5507/jtie.2013.017.

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Krishna, Manne Vamshi, Gopu Abhishek Reddy, B. Prasanthi, and M. Sreevani. "Green Virtual Mouse Using OpenCV." International Journal of Computer Sciences and Engineering 7, no. 4 (April 30, 2019): 575–80. http://dx.doi.org/10.26438/ijcse/v7i4.575580.

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Aditya Lahoty. "Traffic Light Optimization using OpenCV." International Journal for Modern Trends in Science and Technology 6, no. 12 (December 5, 2020): 171–75. http://dx.doi.org/10.46501/ijmtst061233.

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Traffic Light Optimization aims to find the solution for an increased amount of unnecessary waiting time on traffic signals. Traffic Signal Optimization is the process of changing the timing parameters relative to the length of the green light for each traffic movement and the timed relationship between signalized intersections using a computer software program. Our project aims to set the timer of green light based on real-time traffic congestion i.e. number of vehicles in a particular direction of the traffic light. To work in this project, we are using the OpenCV method to detect vehicles and then perform our calculation in the algorithm to predict the time for the green light to be in an active state.

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Lee, Sang-Young. "OpenCV-based Object Tracking System." Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology 6, no. 5 (May 31, 2016): 29–37. http://dx.doi.org/10.14257/ajmahs.2016.05.37.

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Pulli, Kari, Anatoly Baksheev, Kirill Kornyakov, and Victor Eruhimov. "Realtime Computer Vision with OpenCV." Queue 10, no. 4 (April 2012): 40–56. http://dx.doi.org/10.1145/2181796.2206309.

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Bach, Matthias, Volker Lindenstruth, Owe Philipsen, and Christopher Pinke. "Lattice QCD based on OpenCL." Computer Physics Communications 184, no. 9 (September 2013): 2042–52. http://dx.doi.org/10.1016/j.cpc.2013.03.020.

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Condello, Giovanni, Paolo Pasteris, Danilo Pau, and Mariagiovanna Sami. "An OpenCL-based feature matcher." Signal Processing: Image Communication 28, no. 4 (April 2013): 345–50. http://dx.doi.org/10.1016/j.image.2012.06.002.

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D., Kavitha. "Multiple Object Recognition Using OpenCV." Revista Gestão Inovação e Tecnologias 11, no. 2 (June 5, 2021): 1736–47. http://dx.doi.org/10.47059/revistageintec.v11i2.1795.

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For automatic vision systems used in agriculture, the project presents object characteristics analysis using image processing techniques. In agriculture science, automatic object characteristics identification is important for monitoring vast areas of crops, and it detects signs of object characteristics as soon as it occurs on plant leaves. Image content characterization and supervised classifier type neural network are used in the proposed deciding method. Pre-processing, image segmentation, and detection are some of the image processing methods used in this form of decision making. An image data will be rearranged and, if necessary, a region of interest will be selected during preparation. For network training and classification, colour and texture features are extracted from an input. Colour characteristics such as mean and variance in the HSV colour space, as well as texture characteristics such as energy, contrast, homogeneity, and correlation. The device will be trained to automatically identify test images in order to assess object characteristics. With some training samples of that type, an automated classifier NN could be used for classification supported learning in this method. The tangent sigmoid function is used as the kernel function in this network. Finally, the simulated results show that the used network classifier has a low error rate during training and higher classification accuracy. In the previous researches Object detection has been made possible, but in our current research we have attempted to do live Object Detection using OpenCV and also the techniques involved in it.

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Bugaets, A. N. "Using the OpenMI standard for developing integrated systems of hydrological modeling." Russian Meteorology and Hydrology 39, no. 7 (July 2014): 498–506. http://dx.doi.org/10.3103/s1068373914070097.

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Shrestha, Narayan Kumar, Olkeba Tolessa Leta, Bruno De Fraine, Ann van Griensven, and Willy Bauwens. "OpenMI-based integrated sediment transport modelling of the river Zenne, Belgium." Environmental Modelling & Software 47 (September 2013): 193–206. http://dx.doi.org/10.1016/j.envsoft.2013.05.004.

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Buahin, Caleb A., and Jeffery S. Horsburgh. "Advancing the Open Modeling Interface (OpenMI) for integrated water resources modeling." Environmental Modelling & Software 108 (October 2018): 133–53. http://dx.doi.org/10.1016/j.envsoft.2018.07.015.

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