PI: Joe Sventek
The goal of this projects is to prototype to segment 3D objects into equivalence classes using known Deep Learning techniques; understand performance of known techniques.
- Focus on 2D and 3D computer vision images of objects
- Define labelling format for these images
- Understand existing SIFT-based algorithm accuracy and performance
- Apply known Deep Learning techniques, comparing accuracy and performance with SIFT-based techniques
- Produce proof-of-concept Python implementation
- Particularly focus on any obvious patterns exhibited by false positive/negative classifications