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Week 9: Web-Assisted Object Detection

Week 9: Web-Assisted Object Detection. Alejandro Torroella & Amir R. zamir. Sensor Model: Perspective Projection. Implemented a sensor model based on perspective projection (objects that are far away appear smaller in the image as compared to objects that are closer) Where:

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Week 9: Web-Assisted Object Detection

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  1. Week 9:Web-Assisted Object Detection Alejandro Torroella & Amir R. zamir

  2. Sensor Model: Perspective Projection • Implemented a sensor model based on perspective projection (objects that are far away appear smaller in the image as compared to objects that are closer) • Where: • P = pixel transformation matrix • K = camera calibration matrix • R = rotation matrix • C = world coordinate of the camera • Xw = world coordinate of the object • Xi = pixel coordinate of the object

  3. Geometry Method results: Before Street Lights Trash Cans

  4. Geometry Method results: After GIS Sift(without perspective projection) Street Lights Trash Cans

  5. Geometry Method results: After GIS Sift(with perspective projection) Street Lights Trash Cans

  6. Geometry Method results: after Fusion (without perspective projection) Street Lights Trash Cans

  7. Geometry Method results: after Fusion (with perspective projection) Street Lights Trash Cans

  8. Geometry Method results: Before Traffic Signals Street Lights

  9. Geometry Method results: After GIS Sift(without perspective projection) Traffic Signals Street Lights

  10. Geometry Method results: After GIS Sift(with perspective projection) Traffic Signals Street Lights

  11. Geometry Method results: after Fusion (without perspective projection) Traffic Signals Street Lights

  12. Geometry Method results: after Fusion (with perspective projection) Traffic Signals Street Lights

  13. Goals for next week • Test the GIS fusion with perspective projection thoroughly • Possibly fix bugs with the implementation of the sensor model • Principal point of the image is unknown, need some way to find what it is. • Some pixel values result in out of the bounds of the image • Not sure why, but it might be due to the rough estimation of the principal point and/or error in the conversion from geodetic to ECEF.

  14. Thank youFin.

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