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Distributed Real-Time Embedded Video Processing

Distributed Real-Time Embedded Video Processing. Tiehan Lv (1), Burak Ozer (2), Wayne Wolf (1) (1)   Dept. of EE, Princeton University (2)   Verificon Corp. Smart Camera Systems.

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Distributed Real-Time Embedded Video Processing

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  1. Distributed Real-Time Embedded Video Processing Tiehan Lv (1), Burak Ozer (2), Wayne Wolf (1) (1)   Dept. of EE, Princeton University (2)   Verificon Corp.

  2. Smart Camera Systems • A smart camera is a video surveillance system that is able to identify body parts and objects and then recognize the activity of people or objects in the scene.

  3. Sample Scenarios

  4. Algorithms

  5. TriMedia Board TM32 (VLIW) Camera NTSC Shared Memory Host PC SuperScalar RISC CPU PCI Bus TriMedia Board TM32 (VLIW) Camera NTSC Shared Memory Architecture of a Smart Camera System

  6. Multiple Camera Systems • Electronically Panning&Zooming • Occlusion

  7. Centralized Processing Storage Cost Latency Communication Load Power

  8. Centralized Processing vs. Distributed Processing • Raw Data vs. Abstract Representation • Network Load • Energy • Latency • Processing Power

  9. Design Time Decisions and Run-time Decisions • Configuration • Processor • Special Functional Units • Hardware Architecture • Operating System • Efficiency • Flexibility

  10. Distributed Video Middleware • The Concept of Layers • Trans-platform Development • Trans-platform Communication

  11. Distributed Video Middleware

  12. Distributed Video Middleware • Separate video processing algorithm and operating system • Algorithm researcher focus on video processing • Facilitate porting application to different systems

  13. Conclusion and Future Work • Distributed smart camera systems have advantages over traditional centralized processing systems • Design time decisions and run-time decisions need to be combined to form an optimal solution • Distributed video middleware can facilitate research and application development

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