TY - GEN
T1 - 3D object retrieval and pose estimation for a single-view query image in a mobile environment
AU - Tak, Yoon Sik
AU - Hwang, Eenjun
PY - 2011
Y1 - 2011
N2 - 3D object retrieval and its pose estimation for a single view query image are essential operations in many specialized applications. With the recent deployment of various mobile devices, such operations require near real-time performance. However, most of the existing methods are not appropriate for mobile devices, due to their massive resource requirements. In this paper, we propose new 3D object retrieval and pose estimation schemes that can be used on a client-server platform. In order to accomplish this, we first construct both a sparse and a full index on the shape feature of the objects for the client and the server, respectively. Then, the client (the mobile device) retrieves the candidate camera view images that are similar to the query image by using the sparse index. The server refines the results by using the full index and then computes the exact pose by using the SIFT (Scale Invariant Feature Transform) features. In the experiment, we show that our prototype system based on the proposed scheme can achieve an excellent performance.
AB - 3D object retrieval and its pose estimation for a single view query image are essential operations in many specialized applications. With the recent deployment of various mobile devices, such operations require near real-time performance. However, most of the existing methods are not appropriate for mobile devices, due to their massive resource requirements. In this paper, we propose new 3D object retrieval and pose estimation schemes that can be used on a client-server platform. In order to accomplish this, we first construct both a sparse and a full index on the shape feature of the objects for the client and the server, respectively. Then, the client (the mobile device) retrieves the candidate camera view images that are similar to the query image by using the sparse index. The server refines the results by using the full index and then computes the exact pose by using the SIFT (Scale Invariant Feature Transform) features. In the experiment, we show that our prototype system based on the proposed scheme can achieve an excellent performance.
KW - 3D object retrieval
KW - Distance curve
KW - Pose estimation
KW - SIFT
KW - Shape-based retrieval
UR - http://www.scopus.com/inward/record.url?scp=84893320441&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893320441&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84893320441
SN - 9781612081298
T3 - MMEDIA - International Conferences on Advances in Multimedia
SP - 62
EP - 67
BT - MMEDIA 2011 - 3rd International Conferences on Advances in Multimedia
T2 - 3rd International Conferences on Advances in Multimedia, MMEDIA 2011
Y2 - 17 April 2011 through 22 April 2011
ER -