1. Paper Bibliography
- Title: Combining Corners from Multiple Segmenters
- Authors: Aaron Wolin, Martin Field, and Tracy Hammond.
- Publication: Proceedings of the Eighth Eurographics Symposium on Sketch-Based Interfaces and Modeling. ACM, 2011.
2. Summary
- There are several stroke segmentation algorithms. The algorithm attempts to slice strokes into primitives. Combine
Terms
- Feature subset selection
- Sequential floating backward selection(SFBS)
- Mean-squared error(MSE) objective function
- Bookkeepting technique
- Optimal polyline
3. Details
- Previous work
- Corner Subset Selection
- Step 1: Segmenters Used
- Douglas-Peucker
- ShortStraw
- PaleoSketch
- Sezgin
- Kim
- Step 2: Subset Selection
- For dimensionality reduction in pattern classification problems
- Feature = Dimension
- Sequential floating backward selection(SFBS)
- Start with the entire set of feature
- Remove greedy - the least performance
- Add previously removed one - bookkeeping techniques
- Mean-Squared error(MSE)
- Choose which corner to remove
- Step 3: Training and Testing
- Step 1: Segmenters Used
- Douglas-Peucker
- ShortStraw
- PaleoSketch
- Sezgin
- Kim
- Step 2: Subset Selection
- For dimensionality reduction in pattern classification problems
- Feature = Dimension
- Sequential floating backward selection(SFBS)
- Start with the entire set of feature
- Remove greedy - the least performance
- Add previously removed one - bookkeeping techniques
- Mean-Squared error(MSE)
- Choose which corner to remove
- Step 3: Training and Testing
4. Evaluation
- Recall
- Traditional accuracy
This paper presents a good combination of multiple corner finding algorithms. Your paper review shows a good explanation of how they are applied together and how to make a feature subset selection. Nice.
ReplyDeleteA good example of subset selection indeed. In fact I understood the concept after reading this paper only
ReplyDelete