Indoor Location Retrieval using Shape Matching of KinectFusion Scans to Large-Scale Indoor Point Clouds

Eurographics DL Repository

Show simple item record Al-Nuaimi, Anas en_US Piccolrovazzi, Martin en_US Gedikli, Suat en_US Steinbach, Eckehard en_US Schroth, Georg en_US
dc.contributor.editor I. Pratikakis and M. Spagnuolo and T. Theoharis and L. Van Gool and R. Veltkamp en_US 2015-04-27T11:03:34Z 2015-04-27T11:03:34Z 2015 en_US
dc.identifier.uri en_US
dc.description.abstract In this paper we show that indoor location retrieval can be posed as a part-in-whole matching problem of Kinect- Fusion (KinFu) query scans in large-scale target indoor point clouds. We tackle the problem with a local shape feature-based 3D Object Retrieval (3DOR) system. We specifically show that the KinFu queries suffer from artifacts stemming from the non-linear depth distortion and noise characteristics of Kinect-like sensors that are accentuated by the relative largeness of the queries. We furthermore show that proper calibration of the Kinect sensor using the CLAMS technique (Calibrating, Localizing, and Mapping, Simultaneously) proposed by Teichman et al. effectively reduces the artifacts in the generated KinFu scan and leads to a substantial retrieval performance boost. Throughout the paper we use queries and target point clouds obtained at the world's largest technical museum. The target point clouds cover floor spaces of up to 3500m2. We achieve an average localization accuracy of 6cm although the KinFu query scans make up only a tiny fraction of the target point clouds. en_US
dc.publisher The Eurographics Association en_US
dc.subject I.3.3 [Computer Graphics] en_US
dc.subject Picture/Image Generation en_US
dc.subject Line and curve generation en_US
dc.title Indoor Location Retrieval using Shape Matching of KinectFusion Scans to Large-Scale Indoor Point Clouds en_US
dc.description.seriesinformation Eurographics Workshop on 3D Object Retrieval en_US
dc.description.sectionheaders 3D Partial Shape Matching and Retrieval en_US
dc.identifier.doi 10.2312/3dor.20151052 en_US
dc.identifier.pages 31-38 en_US

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