1. Sketch-Based Shape Retrieval M. Eitz, R. Richter, K. Hildebrand, M. Alexa, TU Berlin; T. Boubekeur, Tele ParisTech – CNRS;

2. Outline What is sketch based shape retrieval? Sketch data base Bag-of-features shape retrieval GALIF: Gabor local line-based feature Conclusions & Results

3. What is sketch based shape retrieval? sketch 3D model

4. 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. The sketches are free to download.

5. Sketch data base

6. 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”}

7. 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

8. Bag-of-features shape retrieval

9. 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}

10. 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.

11. For each view direction v i, predict its probability p i = p(v i ) of being a best view. The probability is a smooth scalar field over a sphere and best views are local maxima.

12. GALIF: Gabor local line-based feature Gabor filter : rotate an image by angle

13. 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

14. Local GALIF feature definition I is divided into nxn regions S, t <= n i = 1, 2,..., k. ------ orientataions

15. Conclusions & Results Main differences with our paper: 1.Best view selection 2.Feature representation

16. Results

17. Q&A