elhacker / ptam Goto Github PK
View Code? Open in Web Editor NEWParallel Tracking and Mapping (PTAM) is a camera tracking system for Augmented Reality. It requires no markers, pre-made maps, known templates, or inertial sensors.
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ptam's Issues
Implement BRIEF
Implement rBRIEF
Camera Calibration
Figure out lightning in the scene.
Add Harris corner measure to fast9 detector
Refer to ORB paper for details.
Implement features related to image segmentation
Have 6DOF camera tracking. Rotation and Translation
Identify the Edges of the plane
Investigate the tools and integration of them with Hardware.
Have right scale of computer generated objects into scene
ie. If the camera moves away from the object, the object keeps the right scale
Have 3DOF camera tracking. Only Rotation
Place Computer Generated Object into the environment
Apply a scale pyramid of the image to FAST9
Implement oFAST
Have Depth Map for a single plane in the scene
Implement oFAST
Place Computer Generated Objects into the environment with Occlusions.
For example: a real box in the image blocks a part of a 3D computer generated model.
ORB Feature Detector and Descriptor
Fast9 feature detector
Mapping World Coordinates to Image Coordinates
Fill in the report
Braulio has to fill in:
Sections
2.1 Data Acquisition
2.3 Estimating Camera position
2.5 Augmentation with Virtual Objects
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