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Advanced Real Time Manipulation Of Video Streams
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Book Synopsis Advanced Real-Time Manipulation of Video Streams by : Jan Herling
Download or read book Advanced Real-Time Manipulation of Video Streams written by Jan Herling and published by Springer. This book was released on 2014-05-06 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diminished Reality is a new fascinating technology that removes real-world content from live video streams. This sensational live video manipulation actually removes real objects and generates a coherent video stream in real-time. Viewers cannot detect modified content. Existing approaches are restricted to moving objects and static or almost static cameras and do not allow real-time manipulation of video content. Jan Herling presents a new and innovative approach for real-time object removal with arbitrary camera movements.
Download or read book Games and Ethics written by Maike Groen and published by Springer Nature. This book was released on 2020-11-29 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: The number of digital gamers is increasing worldwide, but public debates about digital games commonly focus on questionable game content or problematic gaming behavior. This book offers a broader ethical perspective on digital game cultures, presenting theoretical and empirical work on the ethical dimensions of the development, production and distribution of digital games, as well as issues relating to responsible gaming and the pedagogical use of digital games. Questions of the communicative-cultural change in game cultures are linked with questions of media education and media ethics. With such a comprehensive approach, the volume promotes ethical discourse on digital game cultures.
Download or read book Video Mining written by Azriel Rosenfeld and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video Video understanding deals with understanding of video understanding. sequences, e.g., recognition of gestures, activities, facial expressions, etc. The main shift in the classic paradigm has been from the recognition of static objects in the scene to motion-based recognition of actions and events. Video understanding has overlapping research problems with other fields, therefore blurring the fixed boundaries. Computer graphics, image processing, and video databases have obvi ous overlap with computer vision. The main goal of computer graphics is to generate and animate realistic looking images, and videos. Re searchers in computer graphics are increasingly employing techniques from computer vision to generate the synthetic imagery. A good exam pIe of this is image-based rendering and modeling techniques, in which geometry, appearance, and lighting is derived from real images using computer vision techniques. Here the shift is from synthesis to analy sis followed by synthesis. Image processing has always overlapped with computer vision because they both inherently work directly with images.
Book Synopsis ADVANCED VIDEO PROCESSING PROJECTS WITH PYTHON AND TKINTER by : Vivian Siahaan
Download or read book ADVANCED VIDEO PROCESSING PROJECTS WITH PYTHON AND TKINTER written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2024-05-27 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on developing Python-based GUI applications for video processing and analysis, catering to various needs such as object tracking, motion detection, and frame analysis. These applications utilize libraries like Tkinter for GUI development and OpenCV for video processing, offering user-friendly interfaces with interactive controls. They provide functionalities like video playback, frame navigation, ROI selection, filtering, and histogram analysis, empowering users to perform detailed analysis and manipulation of video content. Each project tackles specific aspects of video analysis, from simplifying video processing tasks through a graphical interface to implementing advanced algorithms like Lucas-Kanade, Kalman filter, and Gaussian pyramid optical flow for optical flow computation and object tracking. Moreover, they integrate features like MD5 hashing for video integrity verification and filtering techniques such as bilateral filtering, anisotropic diffusion, and denoising for enhancing video quality and analysis accuracy. Overall, these projects demonstrate the versatility and effectiveness of Python in developing comprehensive tools for video analysis, catering to diverse user needs in fields like computer vision, multimedia processing, forensic analysis, and content verification. The first project aims to simplify video processing tasks through a user-friendly graphical interface, allowing users to execute various operations like filtering, edge detection, hashing, motion analysis, and object tracking effortlessly. The process involves setting up the GUI framework using tkinter, adding descriptive titles and containers for buttons, defining button actions to execute Python scripts, and dynamically generating buttons for organized presentation. Functionalities cover a wide range of video processing tasks, including frame operations, motion analysis, and object tracking. Users interact by launching the application, selecting an operation, and viewing results. Advantages include ease of use, organized access to functionalities, and extensibility for adding new tasks. Overall, this project bridges Python scripting with a user-friendly interface, democratizing advanced video processing for a broader audience. The second project aims to develop a video player application with advanced frame analysis functionalities, allowing users to open video files, navigate frames, and analyze them extensively. The application, built using tkinter, features a canvas for video display with zoom and drag capabilities, playback controls, and frame extraction options. Users can jump to specific times, extract frames for analysis, and visualize RGB histograms while calculating MD5 hash values for integrity verification. Additionally, users can open multiple instances of the player for parallel analysis. Overall, this tool caters to professionals in forensic analysis, video editing, and educational fields, facilitating comprehensive frame-by-frame examination and evaluation. The third project is a robust Python tool tailored for video frame analysis and filtering, employing Tkinter for the GUI. Users can effortlessly load, play, and dissect video files frame by frame, with options to extract frames, implement diverse filtering techniques, and visualize color channel histograms. Additionally, it computes and exhibits hash values for extracted frames, facilitating frame comparison and verification. With an array of functionalities, including OpenCV integration for image processing and filtering, alongside features like wavelet transform and denoising algorithms, this application is a comprehensive solution for users requiring intricate video frame scrutiny and manipulation. The fourth project is a robust application designed for edge detection on video frames, featuring a Tkinter-based GUI for user interaction. It facilitates video loading, frame navigation, and application of various edge detection algorithms, alongside offering analyses like histograms and hash values. With functionalities for frame extraction, edge detection selection, and interactive zooming, the project provides a comprehensive solution for users in fields requiring detailed video frame analysis and processing, such as computer vision and multimedia processing. The fifth project presents a sophisticated graphical application tailored for video frame processing and MD5 hashing. It offers users a streamlined interface to load videos, inspect individual frames, and compute hash values, crucial for tasks like video forensics and integrity verification. Utilizing Python libraries such as Tkinter, PIL, and moviepy, the project ensures efficient video handling, metadata extraction, and histogram visualization, providing a robust solution for diverse video analysis needs. With its focus on frame-level hashing and extensible architecture, the project stands as a versatile tool adaptable to various applications in video analysis and content verification. The sixth project presents a robust graphical tool designed for video analysis and frame extraction. By leveraging Python and key libraries like Tkinter, PIL, and imageio, users can effortlessly open videos, visualize frames, and extract specific frames for analysis. Notably, the application computes hash values using eight different algorithms, including MD5, SHA-1, and SHA-256, enhancing its utility for tasks such as video forensics and integrity verification. With features like frame zooming, navigation controls, and support for multiple instances, this project offers a versatile platform for comprehensive video analysis, catering to diverse user needs in fields like content authentication and forensic investigation. The seventh project offers a graphical user interface (GUI) for computing hash values of video files, ensuring their integrity and authenticity through multiple hashing algorithms. Key features include video playback controls, hash computation using algorithms like MD5, SHA-1, and SHA-256, and displaying and saving hash values for reference. Users can open multiple instances to handle different videos simultaneously. The tool is particularly useful in digital forensics, data verification, and content security, providing a user-friendly interface and robust functionalities for reliable video content verification. The eighth project aims to develop a GUI application that lets users interact with video files through various controls, including play, pause, stop, frame navigation, and time-specific jumps. It also offers features like zooming, noise reduction via a mean filter, and the ability to open multiple instances. Users can load videos, adjust playback, apply filters, and handle video frames dynamically, enhancing video viewing and manipulation. The ninth project aims to develop a GUI application for filtering video frames using anisotropic diffusion, allowing users to load videos, apply the filter, and interact with the frames. The core component, AnisotropicDiffusion, handles video processing and GUI interactions. Users can control playback, zoom, and navigate frames, with the ability to apply the filter dynamically. The GUI features panels for video display, control buttons, and supports multiple instances. Event handlers enable smooth interaction, and real-time updates reflect changes in playback and filtering. The application is designed for efficient memory use, intuitive controls, and a responsive user experience. The tenth project involves creating a GUI application that allows users to filter video frames using a bilateral filter. Users can load video files, apply the filter, and interact with the filtered frames. The BilateralFilter class handles video processing and GUI interactions, initializing attributes like the video source and GUI elements. The GUI includes panels for displaying video frames and control buttons for opening files, playback, zoom, and navigation. Users can control playback, zoom, pan, and apply the filter dynamically. The application supports multiple instances, efficient rendering, and real-time updates, ensuring a responsive and user-friendly experience. The twelfth project involves creating a GUI application for filtering video frames using the Non-Local Means Denoising technique. The NonLocalMeansDenoising class manages video processing and GUI interactions, initializing attributes like video source, frame index, and GUI elements. Users can load video files, apply the denoising filter, and interact with frames through controls for playback, zoom, and navigation. The GUI supports multiple instances, allowing users to compare videos. Efficient rendering ensures smooth playback, while adjustable parameters fine-tune the filter's performance. The application maintains aspect ratios, handles errors, and provides feedback, prioritizing a seamless user experience. The thirteenth performs Canny edge detection on video frames. It allows users to load video files, view original frames, and see Canny edge-detected results side by side. The VideoCanny class handles video processing and GUI interactions, initializing necessary attributes. The interface includes panels for video display and control buttons for loading videos, adjusting zoom, jumping to specific times, and controlling playback. Users can also open multiple instances for comparing videos. The application ensures smooth playback and real-time edge detection with efficient rendering and robust error handling. The fourteenth project is a GUI application built with Tkinter and OpenCV for real-time edge detection in video streams using the Kirsch algorithm. The main class, VideoKirsch, initializes the GUI components, providing features like video loading, frame display, zoom control, playback control, and Kirsch edge detection. The interface displays original and edge-detected frames side by side, with control buttons for loading videos, adjusting zoom, jumping to specific times, and controlling playback. Users can play, pause, stop, and navigate through video frames, with real-time edge detection and dynamic frame updates. The application supports multiple instances for comparing videos, employs efficient rendering for smooth playback, and includes robust error handling. Overall, it offers a user-friendly tool for real-time edge detection in videos. The fifteenth project is a Python-based GUI application for computing and visualizing optical flow in video streams using the Lucas-Kanade method. Utilizing tkinter, PIL, imageio, OpenCV, and numpy, it features panels for original and optical flow-processed frames, control buttons, and adjustable parameters. The VideoOpticalFlow class handles video loading, playback, optical flow computation, and error handling. The GUI allows smooth video playback, zooming, time jumping, and panning. Optical flow is visualized in real-time, showing motion vectors. Users can open multiple instances to analyze various videos simultaneously, making this tool valuable for computer vision and video analysis tasks. The sixteenth project is a Python application designed to analyze optical flow in video streams using the Kalman filter method. It utilizes libraries such as tkinter, PIL, imageio, OpenCV, and numpy to create a GUI, process video frames, and implement the Kalman filter algorithm. The VideoKalmanOpticalFlow class manages video loading, playback control, optical flow computation, canvas interactions, and Kalman filter implementation. The GUI layout features panels for original and optical flow-processed frames, along with control buttons and widgets for adjusting parameters. Users can open video files, control playback, and visualize optical flow in real-time, with the Kalman filter improving accuracy by incorporating temporal dynamics and reducing noise. Error handling ensures a robust experience, and multiple instances can be opened for simultaneous video analysis, making this tool valuable for computer vision and video analysis tasks. The seventeenth project is a Python application designed to analyze optical flow in video streams using the Gaussian pyramid method. It utilizes libraries such as tkinter, PIL, imageio, OpenCV, and numpy to create a GUI, process video frames, and implement optical flow computation. The VideoGaussianPyramidOpticalFlow class manages video loading, playback control, optical flow computation, canvas interactions, and GUI creation. The GUI layout features panels for original and optical flow-processed frames, along with control buttons and widgets for adjusting parameters. Users can open video files, control playback, and visualize optical flow in real-time, providing insights into motion patterns within the video stream. Error handling ensures a robust user experience, and multiple instances can be opened for simultaneous video analysis. The eighteenth project is a Python application developed for tracking objects in video streams using the Lucas-Kanade optical flow algorithm. It utilizes libraries like tkinter, PIL, imageio, OpenCV, and numpy to create a GUI, process video frames, and implement tracking functionalities. The ObjectTrackingLucasKanade class manages video loading, playback control, object tracking, GUI creation, and event handling. The GUI layout includes a video display panel with a canvas widget for showing video frames and a list box for displaying tracked object coordinates. Users interact with the video by defining bounding boxes around objects for tracking. The application provides buttons for opening video files, adjusting zoom, controlling playback, and clearing object tracking data. Error handling ensures a smooth user experience, making it suitable for various computer vision and video analysis tasks. The nineteenth project is a Python application utilizing Tkinter to create a GUI for analyzing RGB histograms of video frames. It features the Filter_CroppedFrame class, initializing GUI elements like buttons and canvas for video display. Users can open videos, control playback, and navigate frames. Zooming is enabled, and users can draw bounding boxes for RGB histogram analysis. Filters like Gaussian, Mean, and Bilateral Filtering can be applied, with histograms displayed for the filtered image. Multiple instances of the GUI can be opened simultaneously. The project offers a user-friendly interface for image analysis and enhancement. The twentieth project creates a graphical user interface (GUI) for motion analysis using the Block-based Gradient Descent Search (BGDS) optical flow algorithm. It initializes the VideoBGDSOpticalFlow class, setting up attributes and methods for video display, control buttons, and parameter input fields. Users can open videos, control playback, specify parameters, and analyze optical flow motion vectors between consecutive frames. The GUI provides an intuitive interface for efficient motion analysis tasks, enhancing user interaction with video playback controls and optical flow visualization tools. The twenty first project is a Python project that constructs a graphical user interface (GUI) for optical flow analysis using the Diamond Search Algorithm (DSA). It initializes a VideoFSBM_DSAOpticalFlow class, setting up attributes for video display, control buttons, and parameter input fields. Users can open videos, control playback, specify algorithm parameters, and visualize optical flow motion vectors efficiently. The GUI layout includes canvas widgets for displaying the original video and optical flow result, with interactive functionalities such as zooming and navigating between frames. The script provides an intuitive interface for optical flow analysis tasks, enhancing user interaction and visualization capabilities. The twenty second project "Object Tracking with Block-based Gradient Descent Search (BGDS)" demonstrates object tracking in videos using a block-based gradient descent search algorithm. It utilizes tkinter for GUI development, PIL for image processing, imageio for video file handling, and OpenCV for computer vision tasks. The main class, ObjectTracking_BGDS, initializes the GUI window and implements functionalities such as video playback control, frame navigation, and object tracking using the BGDS algorithm. Users can interactively select a bounding box around the object of interest for tracking, and the application provides parameter inputs for algorithm adjustment. Overall, it offers a user-friendly interface for motion analysis tasks, showcasing the application of computer vision techniques in object tracking. The tenty third project "Object Tracking with AGAST (Adaptive and Generic Accelerated Segment Test)" is a Python application tailored for object tracking in videos via the AGAST algorithm. It harnesses libraries like tkinter, PIL, imageio, and OpenCV for GUI, image processing, video handling, and computer vision tasks respectively. The main class, ObjectTracking_AGAST, orchestrates the GUI setup, featuring buttons for video control, a combobox for zoom selection, and a canvas for displaying frames. The pivotal agast_vectors method employs OpenCV's AGAST feature detector to compute motion vectors between frames. The track_object method utilizes AGAST for object tracking within specified bounding boxes. Users can interactively select objects for tracking, making it a user-friendly tool for motion analysis tasks. The twenty fourth project "Object Tracking with AKAZE (Accelerated-KAZE)" offers a user-friendly Python application for real-time object tracking within videos, leveraging the efficient AKAZE algorithm. Its tkinter-based graphical interface features a Video Display Panel for live frame viewing, Control Buttons Panel for playback management, and Zoom Scale Combobox for precise zoom adjustment. With the ObjectTracking_AKAZE class at its core, the app facilitates seamless video playback, AKAZE-based object tracking, and interactive bounding box selection. Users benefit from comprehensive tracking insights provided by the Center Coordinates Listbox, ensuring accurate and efficient object monitoring. Overall, it presents a robust solution for dynamic object tracking, integrating advanced computer vision techniques with user-centric design. The twenty fifth project "Object Tracking with BRISK (Binary Robust Invariant Scalable Keypoints)" delivers a sophisticated Python application tailored for real-time object tracking in videos. Featuring a tkinter-based GUI, it offers intuitive controls and visualizations to enhance user experience. Key elements include a Video Display Panel for live frame viewing, a Control Buttons Panel for playback management, and a Center Coordinates Listbox for tracking insights. Powered by the ObjectTracking_BRISK class, the application employs the BRISK algorithm for precise tracking, leveraging features like zoom adjustment and interactive bounding box selection. With robust functionalities like frame navigation and playback control, coupled with a clear interface design, it provides users with a versatile tool for analyzing object movements in videos effectively. The twenty sixth project "Object Tracking with GLOH" is a Python application designed for video object tracking using the Gradient Location-Orientation Histogram (GLOH) method. Featuring a Tkinter-based GUI, users can load videos, navigate frames, and visualize tracking outcomes seamlessly. Key functionalities include video playback control, bounding box initialization via mouse events, and dynamic zoom scaling. With OpenCV handling computer vision tasks, the project offers precise object tracking and real-time visualization, demonstrating the effective integration of advanced techniques with an intuitive user interface for enhanced usability and analysis. The twenty seventh project "boosting_tracker.py" is a Python-based application utilizing Tkinter for its GUI, designed for object tracking in videos via the Boosting Tracker algorithm. Its interface, titled "Object Tracking with Boosting Tracker," allows users to load videos, navigate frames, define tracking regions, apply filters, and visualize histograms. The core class, "BoostingTracker," manages video operations, object tracking, and filtering. The GUI features controls like play/pause buttons, zoom scale selection, and filter options. Object tracking begins with user-defined bounding boxes, and the application supports various filters for enhancing video regions. Histogram analysis provides insights into pixel value distributions. Error handling ensures smooth functionality, and advanced filters like Haar Wavelet Transform are available. Overall, "boosting_tracker.py" integrates computer vision and GUI components effectively, offering a versatile tool for video analysis with user-friendly interaction and comprehensive functionalities. The twenty eighth project "csrt_tracker.py" offers a comprehensive GUI for object tracking using the CSRT algorithm. Leveraging tkinter, imageio, OpenCV (cv2), and PIL, it facilitates video handling, tracking, and image processing. The CSRTTracker class manages tracking functionalities, while create_widgets sets up GUI components like video display, control buttons, and filters. Methods like open_video, play_video, and stop_video handle video playback, while initialize_tracker and track_object manage CSRT tracking. User interaction, including mouse event handlers for zooming and ROI selection, is supported. Filtering options like Wiener filter and adaptive thresholding enhance image processing. Overall, the script provides a versatile and interactive tool for object tracking and analysis, showcasing effective integration of various libraries for enhanced functionality and user experience. The twenty ninth project, KCFTracker, is a robust object tracking application with a Tkinter-based GUI. The KCFTracker class orchestrates video handling, user interaction, and tracking functionalities. It sets up GUI elements like video display and control buttons, enabling tasks such as video playback, bounding box definition, and filter application. Methods like open_video and play_video handle video loading and playback, while toggle_play_pause manages playback control. User interaction for defining bounding boxes is facilitated through mouse event handlers. The analyze_histogram method processes selected regions for histogram analysis. Various filters, including Gaussian and Median filtering, enhance image processing. Overall, the project offers a comprehensive tool for real-time object tracking and video analysis. The thirtieth project, MedianFlow Tracker, is a Python application built with Tkinter for the GUI and OpenCV for object tracking. It provides users with interactive video manipulation tools, including playback controls and object tracking functionalities. The main class, MedianFlowTracker, initializes the interface and handles video loading, playback, and object tracking using OpenCV's MedianFlow tracker. Users can define bounding boxes for object tracking directly on the canvas, with real-time updates of the tracked object's center coordinates. Additionally, the project offers various image processing filters, parameter controls for fine-tuning tracking, and histogram analysis of the tracked object's region. Overall, it demonstrates a comprehensive approach to video analysis and object tracking, leveraging Python's capabilities in multimedia applications. The thirty first project, MILTracker, is a Python application that implements object tracking using the Multiple Instance Learning (MIL) algorithm. Built with Tkinter for the GUI and OpenCV for video processing, it offers a range of features for video analysis and tracking. Users can open video files, select regions of interest (ROI) for tracking, and apply various filters to enhance tracking performance. The GUI includes controls for video playback, navigation, and zoom, while mouse interactions allow for interactive ROI selection. Advanced features include histogram analysis of the ROI and error handling for smooth operation. Overall, MILTracker provides a comprehensive tool for video tracking and analysis, demonstrating the integration of multiple technologies for efficient object tracking. The thirty second project, MOSSE Tracker, implemented in the mosse_tracker.py script, offers advanced object tracking capabilities within video files. Utilizing Tkinter for the GUI and OpenCV for video processing, it provides a user-friendly interface for video playback, object tracking, and image analysis. The application allows users to open videos, control playback, select regions of interest for tracking, and apply various filters. It supports zooming, mouse interactions for ROI selection, and histogram analysis of the selected areas. With methods for navigating frames, clearing data, and updating visuals, the MOSSE Tracker project stands as a robust tool for video analysis and object tracking tasks. The thirty third project, TLDTracker, offers a versatile and powerful tool for object tracking using the TLD algorithm. Built with Tkinter, it provides an intuitive interface for video playback, frame navigation, and object selection. Key features include zoom functionality, interactive ROI selection, and real-time tracking with OpenCV's TLD implementation. Users can apply various filters, analyze histograms, and utilize advanced techniques like wavelet transforms. The tool ensures efficient processing, robust error handling, and extensibility for future enhancements. Overall, TLDTracker stands as a valuable asset for both research and practical video analysis tasks, offering a seamless user experience and advanced image processing capabilities. The thirty fourth project, motion detection application based on the K-Nearest Neighbors (KNN) background subtraction method, offers a user-friendly interface for video processing and analysis. Utilizing Tkinter, it provides controls for video playback, frame navigation, and object detection. The MixtureofGaussiansWithFilter class orchestrates video handling, applying filters like Gaussian blur and background subtraction for motion detection. Users can interactively draw bounding boxes to select regions of interest (ROIs), triggering histogram analysis and various image filters. The application excels in its modular design, facilitating easy extension for custom research or application needs, and empowers users to explore video data effectively. The thirty fifth project, "Mixture of Gaussians with Filtering", is a Python script tailored for motion detection in videos using the MOG algorithm alongside diverse filtering methods. Leveraging tkinter for GUI and OpenCV for image processing, it facilitates interactive video playback, frame navigation, and object tracking. With features like adjustable motion detection thresholds and a wide range of filtering options including Gaussian blur, mean blur, and more, users can fine-tune analysis parameters. Object detection, highlighted by bounding boxes and centroid display, coupled with histogram analysis of selected regions, enhances the tool's utility for in-depth video examination. The thirty sixth project, "running_gaussian_average_with_filtering.py", implements motion detection using the Running Gaussian Average algorithm and offers a range of filtering techniques. It employs Tkinter for GUI creation and integrates OpenCV, PIL, imageio, matplotlib, pywt, and numpy modules. The core component, the RunningGaussianAverage class, orchestrates GUI setup, video processing, frame differencing, contour detection, and filtering. The GUI features a canvas for video display, a listbox for object center display, and control buttons for playback, navigation, and threshold adjustment. Mouse events handle zooming and object selection, while histogram analysis and filtering options enrich the analysis capabilities. Overall, it offers a comprehensive tool for motion detection and object tracking with user-friendly interaction and versatile filtering methods. The thirty seventh project, "kernel_density_estimation_with_filtering.py", implements motion detection using Kernel Density Estimation (KDE) alongside diverse filtering techniques, all wrapped in a Tkinter-based GUI for video file interaction and motion visualization. The main class, KDEWithFilter, orchestrates GUI setup, video frame processing, and interaction functionalities. Leveraging libraries like OpenCV, imageio, Matplotlib, PyWavelets, and NumPy, it handles tasks such as video I/O, background subtraction, contour detection, and filtering. Users can open, play/pause/stop videos, navigate frames, adjust thresholds, and apply filters. Mouse-driven ROI selection enables histogram analysis and filter application, while interactive parameter adjustments enhance flexibility. Overall, the script offers a comprehensive tool for motion detection and image filtering, catering to diverse computer vision needs.
Book Synopsis Applications of Evolutionary Computing by : Günther Raidl
Download or read book Applications of Evolutionary Computing written by Günther Raidl and published by Springer Science & Business Media. This book was released on 2004-03-25 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the joint refereed proceedings of six workshops on evolutionary computing, EvoWorkshops 2004, held together with EuroGP 2004 and EvoCOP 2004 in Coimbra, Portugal, in April 2004. The 55 revised full papers presented were carefully reviewed and selected from a total of 123 submissions. In accordance with the six workshops covered, the papers are organized in topical sections on evolutionary bioinformatics; evolutionary computing in communications, networks, and connected systems; hardware optimization techniques; evolutionary computing in image analysis and signal processing; evolutionary music and art; and evolutionary algorithms in stochastic and dynamic environments.
Book Synopsis Videoconferencing by : James R. Wilcox
Download or read book Videoconferencing written by James R. Wilcox and published by Taylor & Francis. This book was released on 2017-09-29 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: First published in 2000. Routledge is an imprint of Taylor & Francis, an informa company.
Book Synopsis Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022 by : Aboul Ella Hassanien
Download or read book Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022 written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2022-11-17 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings book constitutes the refereed proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics (AISI 2021), which took place in Cairo, Egypt, during November 20–22, 2022, and is an international interdisciplinary conference that presents a spectrum of scientific research on all aspects of informatics and intelligent systems, technologies, and applications.
Book Synopsis ENTERprise Information Systems by : Maria Manuela Cruz-Cunha
Download or read book ENTERprise Information Systems written by Maria Manuela Cruz-Cunha and published by Springer. This book was released on 2011-09-30 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume-set (CCIS 219, CCIS 220, and CCIS 221) constitutes the refereed proceedings of the International Conference on ENTERprise Information Systems, CENTERIS 2011, held in Vilamoura, Portugal, in September 2011. The approx. 120 revised full papers presented in the three volumes were carefully reviewed and selected from 180 submissions. The papers are organized in topical sections on knowledge society, EIS adoption and design, EIS implementation and impact, EIS applications, social aspects and IS in education, IT/IS management, telemedicine and imaging technologies, healthcare information management, medical records and business processes, decision support systems and business intelligence in health and social care contexts, architectures and emerging technologies in healthcare organizations, as well as m-health.
Book Synopsis Idiot Engineering by : Alfred Boediman
Download or read book Idiot Engineering written by Alfred Boediman and published by Kesaint Blanc. This book was released on 2020-12-17 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: We all, especially software engineers, are on a journey of enhancing Artificial Intelligence (AI). Some of us have even dedicated our lives to it. Every part of the journey is astonishing, including the challenges we encounter. Our struggles sometimes lead to ineffective outcomes, and because of this, some people consider what we are doing, or what we have done, boring or even idiotic. Nevertheless, this journey would not be fulfilling without all the highs and lows. Whether or not we agree with it, AI is here and here to stay. What we need to do is embrace Artificial Intelligence, and we need to enjoy the journey! But how do we enjoy it? This book will help us do that by explaining the definition of AI, the potentials and the risks of AI, how to work on AI, how to utilize AI, and how to increase AI literacy through education!
Book Synopsis User Centric Media by : Petros Daras
Download or read book User Centric Media written by Petros Daras and published by Springer. This book was released on 2010-05-07 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the First International Conference, UCMedia 2009, which was held on 9-11 December 2009 at Hotel Novotel Venezia Mestre Castellana in Venice, Italy. The conference`s focus was on forms and production, delivery, access, discovery and consumption of user centric media. After a thorough review process of the papers received, 23 were accepted from open call for the main conference and 20 papers for the workshops.
Book Synopsis Advanced Computing by : Natarajan Meghanathan
Download or read book Advanced Computing written by Natarajan Meghanathan and published by Springer. This book was released on 2010-12-25 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the third of three parts of the refereed proceedings of the First International Conference on Computer Science and Information Technology, CCSIT 2010, held in Bangalore, India, in January 2011. The 46 revised full papers presented in this volume were carefully reviewed and selected. The papers are organized in topical sections on soft computing, such as AI, Neural Networks, Fuzzy Systems, etc.; distributed and parallel systems and algorithms; security and information assurance; ad hoc and ubiquitous computing; wireless ad hoc networks and sensor networks.
Book Synopsis Remote and Telerobotics by : Nicolas Mollet
Download or read book Remote and Telerobotics written by Nicolas Mollet and published by BoD – Books on Demand. This book was released on 2010-03-01 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Any book which presents works about controlling distant robotics entities, namely the field of telerobotics, will propose advanced technics concerning time delay compensation, error handling, autonomous systems, secured and complex distant manipulations, etc. So does this new book, Remote and Telerobotics, which presents such state-of-the-art advanced solutions, allowing for instance to develop an open low-cost Robotics platform or to use very efficient prediction models to compensate latency. This edition is organized around eleven high-level chapters, presenting international research works coming from Japan, Korea, France, Italy, Spain, Greece and Netherlands.
Book Synopsis Advanced Lectures on Networking by : Enrico Gregori
Download or read book Advanced Lectures on Networking written by Enrico Gregori and published by Springer. This book was released on 2003-08-02 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the revised version of seven tutorials given at the NETWORKING 2002 Conference in Pisa, Italy in May 2002. The lecturers present a coherent view of the core issues in the following areas: - peer-to-peer computing and communications - mobile computing middleware - network security in the multicast framework - categorizing computing assets according to communication patterns - remarks on ad-hoc networking - communication through virtual technologies - optical networks.
Book Synopsis Advanced Interfacing Techniques for Sensors by : Boby George
Download or read book Advanced Interfacing Techniques for Sensors written by Boby George and published by Springer. This book was released on 2017-04-03 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents ways of interfacing sensors to the digital world, and discusses the marriage between sensor systems and the IoT: the opportunities and challenges. As sensor output is often affected by noise and interference, the book presents effective schemes for recovering the data from a signal that is buried in noise. It also explores interesting applications in the area of health care, un-obstructive monitoring and the electronic nose and tongue. It is a valuable resource for engineers and scientists in the area of sensors and interfacing wanting to update their knowledge of the latest developments in the field and learn more about sensing applications and challenges.
Author :Subhas Chandra Mukhopadhyay Publisher :Springer Science & Business Media ISBN 13 :3319042238 Total Pages :259 pages Book Rating :4.3/5 (19 download)
Book Synopsis Internet of Things by : Subhas Chandra Mukhopadhyay
Download or read book Internet of Things written by Subhas Chandra Mukhopadhyay and published by Springer Science & Business Media. This book was released on 2014-01-25 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advancement in sensor technology, smart instrumentation, wireless sensor networks, miniaturization, RFID and information processing is helping towards the realization of Internet of Things (IoT). IoTs are finding applications in various area applications including environmental monitoring, intelligent buildings, smart grids and so on. This book provides design challenges of IoT, theory, various protocols, implementation issues and a few case study. The book will be very useful for postgraduate students and researchers to know from basics to implementation of IoT.
Book Synopsis Video on Demand Systems by : Shih-Fu Chang
Download or read book Video on Demand Systems written by Shih-Fu Chang and published by Springer. This book was released on 2007-08-28 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: Video on Demand Systems brings together in one place important contributions and up-to-date research results in this fast moving area. Video on Demand Systems serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
Book Synopsis Mastering FreeSWITCH by : Anthony Minessale II
Download or read book Mastering FreeSWITCH written by Anthony Minessale II and published by Packt Publishing Ltd. This book was released on 2016-07-29 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the art of advanced VoIP and WebRTC communication with the most dynamic application server, FreeSWITCH About This Book Forget the hassle - make FreeSWITCH work for you Discover how FreeSWITCH integrates with a range of tools and APIs From high availability to IVR development use this book to become more confident with this useful communication software Who This Book Is For SysAdmins, VoIP engineers – whoever you are, whatever you're trying to do, this book will help you get more from FreeSWITCH. What You Will Learn Get to grips with the core concepts of FreeSWITCH Learn FreeSWITCH high availability Work with SIP profiles, gateways, ITSPs, and Codecs optimization Implement effective security on your projects Master audio manipulation and recording Discover how FreeSWITCH works alongside WebRTC Build your own complex IVR and PBX applications Connect directly to PSTN/TDM Create your own FreeSWITCH module Trace SIP packets with the help of best open source tools Implement Homer Sipcapture to troubleshoot and debug all your platform traffic In Detail FreeSWITCH is one of the best tools around if you're looking for a modern method of managing communication protocols through a range of different media. From real-time browser communication with the WebRTC API to implementing VoIP (voice over internet protocol), with FreeSWITCH you're in full control of your projects. This book shows you how to unlock its full potential – more than just a tutorial, it's packed with plenty of tips and tricks to make it work for you. Written by members of the team who actually helped build FreeSWITCH, it will guide you through some of the newest features of version 1.6 including video transcoding and conferencing. Find out how FreeSWITCH interacts with other tools and APIs, learn how to tackle common (and not so common) challenges ranging from high availability to IVR development and programming advanced PBXs. Great communication functionality begins with FreeSWITCH – find out how and get your project up and running today. Style and approach Find out how it works, then put your knowledge into practice - that's how this advanced FreeSWITCH guide has been designed to help you learn. You'll soon master FreeSWITCH and be confident using it in your projects.