0 - 1 © 2007 Texas Instruments Inc, Content developed in partnership with Tel-Aviv University From MATLAB ® and Simulink ® to Real Time with TI DSPs Video.

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0 - 1 © 2007 Texas Instruments Inc, Content developed in partnership with Tel-Aviv University From MATLAB ® and Simulink ® to Real Time with TI DSPs Video Surveillance with Motion Detection

Slide 2 © 2007 Texas Instruments Inc, Need: Continuous monitoring of scene with video camera –Security (ATM booth, parking lot), Intelligent Highways, Bio/Pharmaceuticals, etc. Problem: Generates large volumes of data to record, archive, and review –Preferable to reduce data stream at the source (embedded compression) Solution: Shrink data storage requirements –Reduce size of each video frame to record, and/or –Reduce total number of video frames to record Simple Idea: Motion within camera’s field of view triggers storage of “interesting” frames Design Requirement: Identify and record only these “interesting” video frames Application: Surveillance Data-Stream Compression

Slide 3 © 2007 Texas Instruments Inc, Principle of Operation  thrsh? Estimate motion energy Record /Displa y Frames Input Frames M Yes

Slide 4 © 2007 Texas Instruments Inc, Principle of Operation Input Frames SAD Display Threshold Display Control Record Absolute Differences Image Trigger Frame Count Display Threshold Display Sum of Absolute Differences (Motion Energy) Display Recorded Image

Slide 5 © 2007 Texas Instruments Inc, Motion Energy Current Frame Previous Frame Motion Energy (Sum of Absolute Differences)

Slide 6 © 2007 Texas Instruments Inc, Source Frames High rate: 30 fps Recorded Frames Aperiodic rate (<< 30 fps) Total # of Recorded Frames The Simulink ® Model

Slide 7 © 2007 Texas Instruments Inc, System Design and Simulation Compare to threshold Record frames & update count Estimate motion Simulink Model Hierarchy

Slide 8 © 2007 Texas Instruments Inc, Compare to threshold Record frames & update count Estimate motion The Simulink Model

Slide 9 © 2007 Texas Instruments Inc, Sum of Absolute Differences Very simple method of inter- frame video motion detection Has efficient fixed-point (integer) implementation in hardware uintN: N-bit unsigned integer intN: N-bit signed integer SAD Algorithm

Slide 10 © 2007 Texas Instruments Inc, Motion levels Video Motion Estimate Detection Threshold Captured Video Frames Motion Detection via Thresholding

Slide 11 © 2007 Texas Instruments Inc, Migration to Real-Time Replace Virtual Sinks/Sources by TCP/IP Receive/Transmit Blocks with Byte Unpack/Pack

Slide 12 © 2007 Texas Instruments Inc, Simulink PC Model Real-time Visualization Host-side visualization Motion Estimates Monitor video capture