A retrieval/classification framework developed to improve accuracy by utilizing population cues.
This was developed as part of my dissertation on shape retrieval. The dissertation will give the most in-depth overview of all algorithms in the framework, while the conference paper covers the most interesting parts
- Improving Shape Classification Using Perceptual and Population Cues - Dissertation (PDF)
- Shape and Image Retrieval by Organizing Instances Using Population Cues - IEEE Workshop on the Applications of Computer Vision (WACV), Clearwater, FL, 2013 (PDF)
Data: SS+IDSC data. Assuming some familiarity with previous works and the MPEG-7 dataset.
The algorithms only need a similiarty matrix that can be used to rank the instances of any dataset.
The driver.py has sample code snippets to illustrate algorithm usage.
Copyright 2013 Andrew Temlyakov. All rights reserved.
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