A Benchmark for Automatic Best View Selection of 3D Objects

BEST VIEW SELECTION corresponds to the task of automatically selecting the most representative view of a 3D model. This benchmark aims to provide tools to evaluate automatic best view selection algorithms. It consists of the preferred viewpoints of 68 models selected by 26 human subjects, and a code to calculate "View selection error". The subjective viewpoints were collected using a web-based subjective experiment where the users were asked to select the most informative view of a 3D model. The 3D object dataset consists of 68 triangular meshes. Some of the models are standard models that are widely used in 3D shape research; and they have been used as test objects by researchers working on the best view problem. A web-based interface is used in the experiments. The user is shown the 68 3D models one at a time. Each model is initially rendered with a random pose. The user is asked to rotate the model via dragging the mouse into a view that he/she thinks is the best, and then to click on the submit button. 26 participants have submitted their preferred best views for the 68 models. For each model, we provide an ASCII file containing the view-points selected by the human subjects. Our evaluations take into account the symmetry sets of the viewpoints. We have used the Fourier-Mellin image matching technique to determine symmetries in the object with respect to a particular view-point. Please Cite the Paper: Dutagaci, Helin, Chun Pan Cheung, and Afzal Godil. "A benchmark for best view selection of 3D objects." Proceedings of the ACM workshop on 3D Object Retrieval. 2010. https://doi.org/10.1145/1877808.1877819

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  "006:55"
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[
  "en"
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  "006:045"
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[
  "https://doi.org/10.1145/1877808.1877819"
]

[
  "Information Technology:Visualization research",
  "Mathematics and Statistics:Image and signal processing"
]