3D zernike descriptors for content based shape retrieval
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
Retrieving articulated 3-d models using medial surfaces and their graph spectra
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
A probabilistic model for component-based shape synthesis
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Learning the compositional structure of man-made objects for 3D shape retrieval
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
3D model retrieval using hybrid features and class information
Multimedia Tools and Applications
On 3D object retrieval benchmarking
3D Research
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When drafting new buildings, architects make intensive use of existing 3D models including building elements, furnishing, and environment elements. These models are either directly included into the draft or serve as a source for inspiration. To allow efficient reuse of existing 3D models, shape retrieval methods considering the specific requirements of architects must be developed. Unfortunately, common 3D shape benchmarks which are used to evaluate the performance of retrieval algorithms are not well suited for architectural data. First, they incorporate models which are not related to this domain, and second and even more important, the provided classification schemes usually do not match an architect's intuition regarding their notion of design and function. To overcome these drawbacks, we present a freely downloadable shape benchmark especially designed for architectural 3D models. It currently contains 2257 objects from various content providers, including companies specialized on 3D CAD applications. All models are classified according to a scheme developed in close cooperation with architects taking into account their specific requirements regarding design and function. Additionally, we show retrieval results for this benchmark using unsupervised and supervised shape retrieval methods and discuss the specific problems regarding retrieval of architectural 3D models.