Retrieval of Objects Captured with Kinect One Camera

Abstract
Low-cost RGB-D sensing technology, such as the Microsoft Kinect, is gaining acceptance in the scientific community and even entering into our homes. This technology enables ordinary users to capture everyday object into digital 3D representations. Considering the image retrieval context, whereas the ability to digitalize photos led to a rapid increase of large collections of images, which in turn raised the need of efficient search and retrieval techniques. We believe the same is happening now for the 3D domain. Therefore, it is essential to identify which 3D shape descriptors, provide better matching and retrieval of such digitalized objects. In this paper, we start by presenting a collection of 3D objects acquired using the latest version of Microsoft Kinect, namely, Kinect One. This dataset, comprising 175 common household objects classified into 18 different classes, was then used for the SHape REtrieval Contest (SHREC). Two groups have submitted their 3D matching techniques, providing the rank list with top 10 results, using the complete set of 175 objects as queries.
Description

        
@inproceedings{
10.2312:3dor.20151068
, booktitle = {
Eurographics Workshop on 3D Object Retrieval
}, editor = {
I. Pratikakis and M. Spagnuolo and T. Theoharis and L. Van Gool and R. Veltkamp
}, title = {{
Retrieval of Objects Captured with Kinect One Camera
}}, author = {
Pascoal, Pedro B.
and
Proença, Pedro
and
Aono, Masaki
and
Gaspar, Filipe
and
Dias, Miguel Sales
and
Teixeira, Filipe
and
Ferreira, Alfredo
and
Seib, Viktor
and
Link, Norman
and
Paulus, Dietrich
and
Tatsuma, Atsushi
}, year = {
2015
}, publisher = {
The Eurographics Association
}, ISBN = {}, DOI = {
10.2312/3dor.20151068
} }
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