VideoForge - PowerPoint PPT Presentation

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VideoForge

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Direct Show , ACML, IPL(IPP), OpenCV, Microsoft Vision SDK, ImageMagick, ... Applications ... usually used to show some information in the image ... – PowerPoint PPT presentation

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Title: VideoForge


1
VideoForge
  • An image processing system

2
Contents
  • Current state of the art
  • Introduction
  • Tiers
  • Base
  • Core
  • Modules
  • User interface
  • Interactive mode
  • Scripting
  • universal interface
  • primary implementation COM scripting object
  • Implementation templates
  • Controllers
  • Algorithms

3
Current state of the art
  • Libraries
  • Loki, Boost
  • Direct Show, ACML, IPL(IPP), OpenCV, Microsoft
    Vision SDK, ImageMagick,
  • Applications
  • GraphEdit (part of the DirectShow)
  • Photoshop
  • ImageJ
  • ImageForge
  • Adobe Premiere,

4
Introduction
  • System for video and live-stream image processing
  • Platform independent
  • ANSI C
  • Easy-to-do computer vision
  • Three tier application
  • Base (Serialization, Communication, Logging)
  • Core (Module management, Memory management)
  • Modules (Devices, Algorithms,)

5
Base
  • Serialization
  • Binary vs. textual storage
  • Automatic vs. manual storage
  • Type lists, storing of arrays, classes
  • Variable reflection
  • offers the possibility of calling the variable
    by name
  • m_plugin.FindVarltintgt(varName)
  • m_plugin.GetVarNames()

6
User interface
  • Communication
  • Scripting possibility
  • User interface (Interactive mode)
  • Types of communication
  • Actions non-parametric methods
  • Properties like variables, accessor methods
  • Methods methods with parameters
  • Events (e.g. onClose, )

7
Core
  • Module and plug-in management
  • Enumeration
  • Registration
  • Memory management
  • Memory (de-)allocation
  • Correct memory handling for erroneous modules
  • Actions (from plug-ins and core itself)
  • User interface handling

8
Modules and plug-ins
  • Module file
  • Contains plug-in implementations
  • compiled-in or represented by DLL
  • Plug-ins
  • Sources
  • Feeds data into chain
  • Algorithms
  • Transforms data, somehow
  • Special plug-ins
  • usually compiled persistence, etc.

9
Image Frame
  • similar to IPL IMAGE structure
  • contains
  • resolution
  • ROI (rectangle of interest)
  • MediaType
  • color mode (rgb, YUV, etc.)
  • bpp (color depth)
  • Frame
  • time information (start, stop time, fps)
  • previous next frame reference (pointer)

10
Building the graph
  • Pipeline building
  • Interactive mode vs. non-interactive mode
  • Device (Controller Device enumerator)
  • Algorithms (Algorithm chain Composite algs)

11
System windows
  • Windows
  • show graphical information
  • part of a particular plugin
  • Bitmap windows
  • shows contents of an image buffer
  • Vector windows
  • usually used to show some information in the
    image
  • applied as a second layer onto the bitmap window
  • Window events
  • OnClose,

12
Templates (1/3)
  • Application template
  • UI application
  • Console application
  • Module template
  • default implementation
  • rare modification
  • implements a list of plug-ins

13
Templates (2/3)
  • Controller template
  • Implement source enumeration
  • Implement data feed
  • Possibly implement UI
  • Algorithm template
  • Implement data transformation
  • Possibly implement UI
  • User must implement 1 method

14
Conclusion
  • We proposed system for implementation of image
    processing and computer vision tasks
  • as platform-independent as possible (ANSI C)
  • consists of (lightweight) core and plugins
  • offers a user interactive, scriptable user
    interface
  • offers various templates for fast implementation
  • The system is a part of various grants
  • Grant UK
  • APVV Grant

15
Future work
  • Finalize implementation of the core with the
    basic modules (12/05)
  • basic image processing operations
  • Implementation of basic modules of 0(1/06)
  • working set optimization
  • Implementation of special modules (06/06)
  • Feature tracking
  • Cooperation with avatars
  • Statistics classifier training
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