SHREC'12 Track: Sketch-Based 3D Shape Retrieval

Sketch-based 3D shape retrieval has become an important research topic in content-based 3D object retrieval. The aim of this track is to measure and compare the performance of sketch-based 3D shape retrieval methods implemented by different participants over the world. The track is based on a new sketch-based 3D shape benchmark, which contains two types of sketch queries and two versions of target 3D models. In this track, 7 runs have been submitted by 5 groups and their retrieval accuracies were evaluated using 7 commonly used retrieval performance metrics. We hope that the benchmark, its corresponding evaluation code, and the comparative evaluation results of the state-of-the-art sketch-based 3D model retrieval algorithms will contribute to the progress of this research direction for the 3D model retrieval community.

[1]  H. Kuhn The Hungarian method for the assignment problem , 1955 .

[2]  J. G. Snodgrass,et al.  A standardized set of 260 pictures: norms for name agreement, image agreement, familiarity, and visual complexity. , 1980, Journal of experimental psychology. Human learning and memory.

[3]  Michael A. Saunders,et al.  Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..

[4]  Michael Elad,et al.  Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[5]  Adam Finkelstein,et al.  Suggestive contours for conveying shape , 2003, ACM Trans. Graph..

[6]  Thomas A. Funkhouser,et al.  The Princeton Shape Benchmark , 2004, Proceedings Shape Modeling Applications, 2004..

[7]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[8]  Rajat Raina,et al.  Efficient sparse coding algorithms , 2006, NIPS.

[9]  Adam Finkelstein,et al.  Where do people draw lines? , 2008, ACM Trans. Graph..

[10]  Sang Min Yoon,et al.  Automatic skeleton extraction and splitting of target objects , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[11]  Ryutarou Ohbuchi,et al.  Dense sampling and fast encoding for 3D model retrieval using bag-of-visual features , 2009, CIVR '09.

[12]  Ryutarou Ohbuchi,et al.  Scale-weighted dense bag of visual features for 3D model retrieval from a partial view 3D model , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

[13]  T. Funkhouser,et al.  How well do line drawings depict shape? , 2009, SIGGRAPH '09.

[14]  Marc Alexa,et al.  Sketch-based 3D shape retrieval , 2010, SIGGRAPH '10.

[15]  Arjan Kuijper,et al.  Sketch-based 3D model retrieval using diffusion tensor fields of suggestive contours , 2010, ACM Multimedia.

[16]  Benjamin Bustos,et al.  An Improved Histogram of Edge Local Orientations for Sketch-Based Image Retrieval , 2010, DAGM-Symposium.

[17]  Bo Li,et al.  View Context: A 3D Model Feature for Retrieval , 2010, MMM.

[18]  Harold W. Kuhn,et al.  The Hungarian method for the assignment problem , 1955, 50 Years of Integer Programming.

[19]  Jitendra Malik,et al.  Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[20]  Marc Alexa,et al.  Sketch-Based Image Retrieval: Benchmark and Bag-of-Features Descriptors , 2011, IEEE Transactions on Visualization and Computer Graphics.

[21]  Arjan Kuijper,et al.  View-based 3D model retrieval using compressive sensing based classification , 2011, 2011 7th International Symposium on Image and Signal Processing and Analysis (ISPA).

[22]  Tobias Schreck,et al.  Sketch-based 3D Model Retrieval using Keyshapes for Global and Local Representation , 2012, 3DOR@Eurographics.

[23]  Ryutarou Ohbuchi,et al.  SHREC'12 Track: Generic 3D Shape Retrieval , 2012, 3DOR@Eurographics.

[24]  Bo Li,et al.  Sketch-based 3D model retrieval by incorporating 2D-3D alignment , 2012, Multimedia Tools and Applications.