IJG  Vol.5 No.11 , October 2014
Two-Edge-Corner Image Features for Registration of Geospatial Images with Large View Variations
ABSTRACT
This paper presents a robust image feature that can be used to automatically establish match correspondences between aerial images of suburban areas with large view variations. Unlike most commonly used invariant image features, this feature is view variant. The geometrical structure of the feature allows predicting its visual appearance according to the observer’s view. This feature is named 2EC (2 Edges and a Corner) as it utilizes two line segments or edges and their intersection or corner. These lines are constrained to correspond to the boundaries of rooftops. The description of each feature includes the two edges’ length, their intersection, orientation, and the image patch surrounded by a parallelogram that is constructed with the two edges. Potential match candidates are obtained by comparing features, while accounting for the geometrical changes that are expected due to large view variation. Once the putative matches are obtained, the outliers are filtered out using a projective matrix optimization method. Based on the results of the optimization process, a second round of matching is conducted within a more confined search space that leads to a more accurate match establishment. We demonstrate how establishing match correspondences using these features lead to computing more accurate camera parameters and fundamental matrix and therefore more accurate image registration and 3D reconstruction.

Cite this paper
Saeedi, P. and Mao, M. (2014) Two-Edge-Corner Image Features for Registration of Geospatial Images with Large View Variations. International Journal of Geosciences, 5, 1324-1344. doi: 10.4236/ijg.2014.511109.
References
[1]   Xiao, J. and Shah, M. (2003) Two-Frame Wide Baseline Matching. Proceedings of the 9th IEEE International Conference on Computer Vision (ICCV 2003), Nice, 14-17 October 2003, 603-609.

[2]   Lowe, D.G. (2004) Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 60, 91-110.
http://dx.doi.org/10.1023/B:VISI.0000029664.99615.94

[3]   Mikolajczyk, K. and Schmid, C. (2001) Indexing Based on Scale Invariant Interest Points. Proceedings of the 8th IEEE International Conference on Computer Vision (ICCV 2001), Vancouver, 7-14 July 2001, 525-531.

[4]   Mikolajczyk, K. and Schmid, C. (2002) An Affine Invariant Interest Point Detector. Proceedings of the 7th European Conference on Computer Vision Part I, Copenhagen, 28-31 May 2002, 128-142.

[5]   Mikolajczyk, K. and Schmid, C. (2004) Scale & Affine Invariant Interest Point Detectors. International Journal of Computer Vision, 60, 63-86.
http://dx.doi.org/10.1023/B:VISI.0000027790.02288.f2

[6]   Tuytelaars, T. and Gool, L.J.V. (2004) Matching Widely Separated Views Based on Affine Invariant Regions. International Journal of Computer Vision, 59, 61-85.
http://dx.doi.org/10.1023/B:VISI.0000020671.28016.e8

[7]   Matas, J., Chum, O., Urban, M. and Pajdla, T. (2002) Robust Wide Baseline Stereo from Maximally Stable Extremal regions. Image and Vision Computing, 22, 761-767.

[8]   Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T. and Gool, L.J.V. (2005) A Comparison of Affine Region Detectors. International Journal of Computer Vision, 65, 43-72.
http://dx.doi.org/10.1007/s11263-005-3848-x

[9]   Ferrari, V., Tuytelaars, T. and Gool, L.J.V. (2003) Wide-Baseline Multiple-View Correspondences. Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Madison, 18-20 June 2003, 718-728.

[10]   Xie, J. and Tsui, H.-T. (2004) Wide Baseline Stereo Matching by Corner-Edge-Regions. Proceedings of the International Conference on Image Analysis and Recognition, Porto, 29 September 2004-1 October 2004, 713-720.

[11]   Schmid, C. and Zisserman, A. (1997) Automatic Line Matching across Views. Proceedings of the 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, 17-19 June 1997, 666-671.

[12]   Bay, H., Ferrari, V. and Gool, L.J.V. (2005) Wide-Baseline Stereo Matching with Line Segments. Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, 20-25 June 2005, 329-336.

[13]   Wang, L., Neumann, U. and You, S. (2009) Wide-Baseline Image Matching Using Line Signatures. Proceedings of the 12th International Conference on Computer Vision, Kyoto, 29 September 2009-2 October 2009, 1311-1318.

[14]   Tell, D. and Carlsson, S. (2002) Combining Appearance and Topology for Wide Baseline Matching. Proceedings of the 7th European Conference on Computer Vision, Copenhagen, 28-31 May 2002, 68-81.

[15]   Ng, E.S. and Kingsbury, N.G. (2010) Matching of Interest Point Groups with Pairwise Spatial Constraints. Proceedings of the 17th IEEE International Conference on Image Processing (ICIP), Hong Kong, 26-29 September 2010, 2693-2696.

[16]   Mortensen, E.N., Deng, H. and Shapiro, L.G. (2005) A SIFT Descriptor with Global Context. Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, 20-25 June 2005, 184-190.

[17]   Lee, J.A., Yow, K.C. and Chia, A.Y.S. (2009) Robust Matching of Building Facades under Large Viewpoint Changes. Proceedings of the 12th International Conference on Computer Vision, Kyoto, 29 September 2009-2 October 2009, 1258-1264.

[18]   Ding, M., Lyngbaek, K. and Zakhor, A. (2008) Automatic Registration of Aerial Imagery with Untextured 3DLiDAR Models. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, 23-28 June 2008, 1-8.

[19]   Wang, L. and Neumann, U. (2009) A Robust Approach for Automatic Registration of Aerial Images with Untextured Aerial LiDAR Data. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Miami, 20-25 June 2009, 2623-2630.

[20]   Burns, J., Hanson, A. and Riseman, E. (1986) Extracting Straight Lines. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8, 425-455.
http://dx.doi.org/10.1109/TPAMI.1986.4767808

[21]   Izadi, M. and Saeedi, P. (2012) Three-Dimensional Polygonal Building Model Estimation from Single Satellite Images. IEEE Transactions on Geoscience and Remote Sensing, 50, 2254-2272.
http://dx.doi.org/10.1109/TGRS.2011.2172995

[22]   Harris, C. and Stephens, M. (1988) A Combined Corner and Edge Detector. Proceedings of the 4th Alvey Vision Conference, Manchester, 31 August-2 September 1988, 147-151.

[23]   Hartley, R. and Zisserman, A. (2003) Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge.

[24]   Mularie, W. (2000) Department of Defense World Geodetic System 1984, Its Definition and Relationships with Local Geodetic Systems, National Geospatial-Intelligence Agency, Technical Report.

[25]   Lowe, D.G. (1999) Object Recognition from Local Scale-Invariant Features. Proceedings of the 7th IEEE International Conference on Computer Vision, Kerkyra, 20-27 September 1999, 1150-1157.

[26]   Bay, H., Tuytelaars, T. and Gool, L.J.V. (2006) SURF: Speeded up Robust Features. Proceedings of the 9th European Conference on Computer Vision, Graz, 7-13 May 2006, 404-417.

[27]   Morel, J.M. and Yu, G. (2009) ASIFT: A New Framework for Fully Affine Invariant Image Comparison. SIAM Journal on Imaging Sciences, 2, 438-469.
http://dx.doi.org/10.1137/080732730

 
 
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