cenas

 

Introductory summary

 

The objective of this SHREC track is to retrieve 3D models captured with a commodity low-cost depth scanner. This dataset, comprised by 192 models, was captured with the Microsoft Kinect camera. As can be seen by the sample presented in the picture above, these models are much rougher than the standard meshes presented in the previous editions of the Shape Retrieval Contest.

 

The advent of low-cost scanners in the consumer market, such as the Microsoft Kinect, has made this technology available to the everyday user. While designed for a different purpose, such devices have proven to be able to digitize 3D objects with acceptable quality, at least considering a myriad of contexts where before the presence of 3D capturing devices was virtually null. As a result, the proliferation of 3D models in the Internet is growing and expected to keep growing as new and innovative ways of capture and sharing 3D information are trusted to develop in the future, taking advantage of cheaper and powerful technology.

 

 

Task description

 

In response to a given set of 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. The query set is a subset of the larger collection.

 

 

Ranked lists


Each file representing an evaluation should be named %id-%query where %id is the number of the run and %query is the identifier of the object representing the query. Please submit the results on any ASCII file format such as '.res'.

Example (for a faux query 144.off):

144    1.00000
24      0.87221
45      0.79915
201    0.59102
203    0.54902
32      0.51241
...(etc)...


This would output in a file named, for instance 1-144.res

 

 

Data set

 

The collection is composed of 192 scanned models, which were acquired through the real-time capture of 224 collected objects. Of these, 32 were rejected due to low quality or material incompability. The range images are captured using a Microsoft Kinect camera. The collection is presented in three different ASCII file formats: PLY, OFF and STL, representing the scans in a triangular mesh.

 

The collection itself is uncategorized. The rankings are to be compared against a human-generated ground truth created with a group of 20 subjects.

 

A test set is available here: here

 

 

Evaluation Methodology

 

We will employ the following evaluation measures: Precision-Recall curve; E-Measure; Discounted Cumulative Gain; Nearest Neighbor, First-Tier (Tier1) and Second-Tier (Tier2).

 

 

Procedure

 

The following list is a description of the activities:

 

 

 

Schedule

 

February 7 - A test set will be available on line. This will be a subset of the final set.
February 11 - Please register before this date.
February 11 - Distribution of the final query sets. Participants can start the retrieval.
February 18 - Submission of results (ranked lists) and a one page description of their method(s).
February 20 - Distribution of relevance judgments (Human-generated) and evaluation scores.
February 25 - Submission of final descriptions (two page) for the contest proceedings.
February 28 - Track is finished, and results are ready for inclusion in a track report
March 29 - Camera ready track papers submitted for printing
May 11 - EUROGRAPHICS Workshop on 3D Object Retrieval including SHREC'2013

 

 

 

  Any further questions can be sent to shrec@3dorus.ist.utl.pt