Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
ACM Transactions on Graphics (TOG)
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
SMI '04 Proceedings of the Shape Modeling International 2004
Shape Complexity Based on Mutual Information
SMI '05 Proceedings of the International Conference on Shape Modeling and Applications 2005
3D-Model search engine from photos
Proceedings of the 6th ACM international conference on Image and video retrieval
3D Object Detection and Viewpoint Selection in Sketch Images Using Local Patch-Based Zernike Moments
CBMI '09 Proceedings of the 2009 Seventh International Workshop on Content-Based Multimedia Indexing
Sketch-based 3D shape retrieval
ACM SIGGRAPH 2010 Talks
Sketch-based 3D model retrieval using diffusion tensor fields of suggestive contours
Proceedings of the international conference on Multimedia
SMI 2011: Full Paper: On visual complexity of 3D shapes
Computers and Graphics
Sketch-Based Image Retrieval: Benchmark and Bag-of-Features Descriptors
IEEE Transactions on Visualization and Computer Graphics
View context: a 3D model feature for retrieval
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
SHREC'12 track: sketch-based 3D shape retrieval
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
Sketch-based 3D model retrieval by incorporating 2D-3D alignment
Multimedia Tools and Applications
SHREC'13 track: large scale sketch-based 3D shape retrieval
3DOR '13 Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval
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Searching for relevant 3D models based on hand-drawn sketches is both intuitive and important for many applications, such as sketch-based 3D modeling and recognition. We propose a sketch-based 3D model retrieval algorithm by utilizing viewpoint entropy-based adaptive view clustering and shape context matching. Different models have different visual complexities, thus there is no need to keep the same number of representative views for each model. Motivated by this, we propose to measure the visual complexity of a 3D model by utilizing viewpoint entropy distribution of a set of sample views and based on the complexity value, we can adaptively decide the number of representative views. Finally, we perform Fuzzy C-Means based view clustering on the sample views based on their viewpoint entropy values. We test our algorithm on two latest sketch-based 3D model retrieval benchmarks and compare it with other four state-of-the-art approaches. The results demonstrate the superior performance and advantages of our algorithm.