The objective of this shape retrieval contest is to retrieve 3D models those are relevant to a query range scan. This task corresponds to a real life scenario where the query is a 3D range scan of an object acquired from an arbitrary view direction. The algorithm should retrieve the relevant 3D objects from a database.
Task description:
In response to a given set of range scan queries, the task is to evaluate similarity scores with the target models and return an ordered ranked list along with the similarity scores for each query.
Data set:
The query set is composed of at least 180 range images, which are acquired by capturing 3 or 4 range scans of 60 models from arbitrary view directions. The range images are captured using a Minolta Laser Scanner. The file format is in the ASCII Object File Format (*.off) representing the scan in a triangular mesh.
The target database contains 1200 complete 3D models, which are categorized into 60 classes. In each class there are 20 models. The file format to represent the 3D models is the ASCII Object File Format (*.off).
Evaluation Methodology:
We will employ the following evaluation measures: Precision-Recall curve; Average Precision (AP) and Mean Average Precision (MAP); E-Measure; Discounted Cumulative Gain; Nearest Neighbor, First-Tier (Tier1) and Second-Tier (Tier2).
Please Cite the Paper: Godil A, Dutagaci H, Bustos B, Choi S, Dong S, Furuya T, Li H, Link N, Moriyama A, Meruane R, Ohbuchi R. SHREC'15: range scans based 3D shape retrieval. In Proceedings of the Eurographics Workshop on 3D Object Retrieval, Zurich, Switzerland 2015 May 3 (pp. 2-3). https://doi.org/10.5555/2852282.2852312
About this Dataset
| Title | SHREC'15: Range Scans based 3D Shape Retrieval |
|---|---|
| Description | The objective of this shape retrieval contest is to retrieve 3D models those are relevant to a query range scan. This task corresponds to a real life scenario where the query is a 3D range scan of an object acquired from an arbitrary view direction. The algorithm should retrieve the relevant 3D objects from a database. Task description: In response to a given set of range scan queries, the task is to evaluate similarity scores with the target models and return an ordered ranked list along with the similarity scores for each query. Data set: The query set is composed of at least 180 range images, which are acquired by capturing 3 or 4 range scans of 60 models from arbitrary view directions. The range images are captured using a Minolta Laser Scanner. The file format is in the ASCII Object File Format (*.off) representing the scan in a triangular mesh. The target database contains 1200 complete 3D models, which are categorized into 60 classes. In each class there are 20 models. The file format to represent the 3D models is the ASCII Object File Format (*.off). Evaluation Methodology: We will employ the following evaluation measures: Precision-Recall curve; Average Precision (AP) and Mean Average Precision (MAP); E-Measure; Discounted Cumulative Gain; Nearest Neighbor, First-Tier (Tier1) and Second-Tier (Tier2). Please Cite the Paper: Godil A, Dutagaci H, Bustos B, Choi S, Dong S, Furuya T, Li H, Link N, Moriyama A, Meruane R, Ohbuchi R. SHREC'15: range scans based 3D shape retrieval. In Proceedings of the Eurographics Workshop on 3D Object Retrieval, Zurich, Switzerland 2015 May 3 (pp. 2-3). https://doi.org/10.5555/2852282.2852312 |
| Modified | 2015-02-06 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | Range Scans , 3D Shape Retrieval , 3D Models , Evaluation and Measurement Science |
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