TY - GEN
T1 - Towards location recognition using range images
AU - Al-Nuaimi, A.
AU - Huitl, R.
AU - Taifour, S.
AU - Sarin, S.
AU - Song, X.
AU - Gu, Y. X.
AU - Steinbach, E.
AU - Fahrmair, M.
PY - 2013
Y1 - 2013
N2 - Retrieving the location of a mobile device by matching a query image to a database of geo-tagged imagery is one popular application of content-based image retrieval (CBIR). Standard CBIR-based approaches exploit appearance features of the environment for the matching process. Many locations, however, are characterized by distinct structural (geometric) features. We investigate whether a standard appearance-based CBIR pipeline can be adapted to perform location retrieval using a range image-based representation of the environment. The contributions are three-fold: We design a rigorous experimental setup using an extensive and challenging indoor dataset. Secondly, we compare the state-of-the-art feature algorithm specifically designed for range images, the Normal Aligned Radial Feature (NARF) [1], against some of the most established appearance-based features. Thirdly, we combine the high key point detection rate of NARF, with the robustness of the Speeded-Up Robust Feature for range-image based location recognition. This detector-descriptor combination, which we coin NURF, leads to 15% improvement in absolute location recognition performance compared to simple NARF in our experimental setup.
AB - Retrieving the location of a mobile device by matching a query image to a database of geo-tagged imagery is one popular application of content-based image retrieval (CBIR). Standard CBIR-based approaches exploit appearance features of the environment for the matching process. Many locations, however, are characterized by distinct structural (geometric) features. We investigate whether a standard appearance-based CBIR pipeline can be adapted to perform location retrieval using a range image-based representation of the environment. The contributions are three-fold: We design a rigorous experimental setup using an extensive and challenging indoor dataset. Secondly, we compare the state-of-the-art feature algorithm specifically designed for range images, the Normal Aligned Radial Feature (NARF) [1], against some of the most established appearance-based features. Thirdly, we combine the high key point detection rate of NARF, with the robustness of the Speeded-Up Robust Feature for range-image based location recognition. This detector-descriptor combination, which we coin NURF, leads to 15% improvement in absolute location recognition performance compared to simple NARF in our experimental setup.
KW - CBIR
KW - NARF
KW - Range Image
KW - SURF
UR - http://www.scopus.com/inward/record.url?scp=84888244127&partnerID=8YFLogxK
U2 - 10.1109/ICMEW.2013.6618361
DO - 10.1109/ICMEW.2013.6618361
M3 - Conference contribution
AN - SCOPUS:84888244127
SN - 9781479916047
T3 - Electronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013
BT - Electronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013
T2 - 2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013
Y2 - 15 July 2013 through 19 July 2013
ER -