RGBD Research Project

OverView

• Building RGB additive color with supervised machine learning.

Multi-View 3D visualization

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• Original Input image from three POV, which will be masked by depth data. Then OpenCV filtering.

• origin author PoKong Lai

• Visualizating the 3D output to ensure the Camera Poses was properly predicted.

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• This Visualizes the environment with three relative camera locations.

• The major challenges is how to synchronizes these camera. So we uses SLAM and VR point-cloud scattering to predict the poses.

Preprocessing

• Recording a person from three point of views. And perform loop closure to predict the camera poses of these POV.

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    • This is the initial mask that will be selected. For each image we will compute similarity to pick the most same components as filter.

Result Video

• network architecture

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• link for result in prediction of backward image from front image.

  • left most column is input, middle is ground truth and last is prediction.
  • feed front image hence left most to AutoEncoder to generate backward image.

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