### Sketch-Based Shape Retrieval

```Sketch-Based Shape Retrieval
M. Eitz, R. Richter, K. Hildebrand, M. Alexa, TU Berlin;
T. Boubekeur, Tele ParisTech – CNRS;
Outline
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What is sketch based shape retrieval?
Sketch data base
Bag-of-features shape retrieval
GALIF: Gabor local line-based feature
Conclusions & Results
What is sketch based shape retrieval?
•
sketch
3D model
Sketch data base
• Based on the Princeton Shape Benchmark
(PSB), authors gather a lot of sketches.
• Analysis result: users mostly sketch objects
from a simple side or frontal view.
Sketch data base
Bag-of-features shape retrieval
• Assuming there are two documents:
1. Bob likes to play basketball, Jim likes too
2. Bob also likes to play football games.
• Construct a Dictionary:
– Dictionary = {1:”Bob”, 2. “like”, 3. “to”, 4. “play”, 5.
“basketball”, 6. “also”, 7. “football”, 8. “games”, 9.
“Jim”, 10. “too”}
Bag-of-features shape retrieval
• The two documents can be encoded by:
① [1, 2, 1, 1, 1, 0, 0, 0, 1, 1]
② [1, 1, 1, 1 ,0, 1, 1, 1, 0, 0]
counts
Bag-of-features shape retrieval
Best-view selection
• Uniformly distributed views:
1. Select d seeds on a unit sphere,
2. Lloyd relaxations iteratively,
3. d Voronoi cell centers as d view directions.
4. d ={22; 52; 102; 202}
Perceptually best views
Training set: manually define best and worst
viewpoints in PSB
Learn a “best view classifier” from the training set
using SVM.
Learn some best viewpoints based on the uniform
viewpoints.
• For each view direction vi , predict its
probability pi = p(vi) of being a best view.
• The probability is a smooth scalar field over a
sphere and best views are local maxima.
GALIF: Gabor local line-based feature
• Gabor filter
: rotate an image by angle 
Orientation-selective filter bank
Given k different orientations, we can
compute k different images:
• (i)dft is the (inverse) discrete Fourier
transformation
• I --- input sketch
• * --- point-wise multiplication
Local GALIF feature definition
• I is divided into nxn regions
• S, t <= n
• i = 1, 2, ..., k. ------ orientataions
Conclusions & Results
• Main differences with our paper:
1. Best view selection
2. Feature representation
Results
Q&A
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