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Vehicle/pedestrian tracking using multiple cameras and JetsonNanos

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JetTrack - MA_Intersection_Calculation

MA_Intersection_Calculation is JetTrack's main algorithmus for real time object position calculation.

Overview:

  • Input-Data: Kafka Data Streams form the JetTrack - MA_DeepStream_Pipeline (running on each camera)
  • Output-Data: Position of all objects in scene, which are detected by the deepstream pipeline

Development

  1. Start KafkaBroker on local Network @ 10.42.0.1:9092 or wherever you want
  2. Start MA_DeepStream_Pipeline on JetsonNano Devices
  3. Adust to your CameraParameters in src/config.json
    • Resolution of detection stream
    • Translation vector of camera (eg. see OpenCV camera calibration)
    • Rotation vector of camera (eg. see OpenCV camera calibration)
    • intrinsicMatrix
    • pathToCalibrationFile (for realtime use of camera calibration files - cam mode)
    • distCoeefs (k1, k2, p1, p2,[,k3,[,k4,k5,k6]]) (eg. see OpenCV camera calibration )
  4. Run main.py on localDevice (connected to CamNetwork or on JetsonDevice itself)

For running Realtime Object Positioning:

  • source: local -> src/config.json, cams -> settings on cams webserver will be used
  • method: aruco -> realign aruco marker to world coordinate system
$ python3 main.py source method

Todos

  • Add more calibrationModes for realingment of different CalibrationObjects

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Vehicle/pedestrian tracking using multiple cameras and JetsonNanos

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