ACM Transactions on Graphics (TOG)
Apparent ridges for line drawing
ACM SIGGRAPH 2007 papers
SHREC'12 track: sketch-based 3D shape retrieval
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
Line image signature for scene understanding with a wearable vision system
Proceedings of the 4th International SenseCam & Pervasive Imaging Conference
A comparison of methods for sketch-based 3D shape retrieval
Computer Vision and Image Understanding
Sketch-based 3D model retrieval by viewpoint entropy-based adaptive view clustering
3DOR '13 Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval
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As large collections of 3D models are starting to become as common as public image collections, the need arises to quickly locate models in such collections. Models are often insufficiently annotated such that a keyword based search is not promising. Our approach for content based searching of 3D models relies entirely on visual analysis and is based on the observation that a large part of our perception of shapes stems from their salient features, usually captured by dominant lines in their display. Recent research on such feature lines has shown that 1) people mostly draw the same lines when asked to depict a certain model and 2) the shape of an object is well represented by the set of feature lines generated by recent NPR line drawing algorithms [Cole et al. 2009]. Consequently, we suggest an image based approach for 3D shape retrieval, exploiting the similarity of human sketches and the results of current line drawing algorithms. Our search engine takes a sketch of the desired model drawn by a user as the input and compares this sketch to a set of line drawings automatically generated for each of the models in the collection.