Computer Vision

Object Tracking and Prediction

  • ●  Built both location classifier and scale classifier.
  • ●  Built parallel pipeline for multiple targets tracking.
  • ●  Conducted test on overlap targets tracking.
  • ●  Combined Appearance-based tracking with Kalman filter.
  • ●  Added a work-around approach for handling occlusions.
  • ●  Calculated and predicted the motion and position when occlusion is assumed.

3D point cloud semantic segmentation

Parsing Point Cloud into Disjoint Spaces

● Detection incorporating void spaces
○ Detecting the peak-gap-peak pattern ○ Merging

● Canonical Coordinate System Among Spaces
Semantic blocks to pixel level boundary segmentation

  • ●  Enforcing Contextual Consistency using CRF
  • ●  Updating the Disjoint Space Parsing Results

 

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s