Weinmann et al. - 2015 - Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers.txt
References start at 2146, end at 2444
Total references: 100
Reference type seems to be ReferenceType.NAMED
Square refs: 0, dotted refs: 13, named refs: 398, trigraph refs: 0
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2: scanner point clouds using local variance information. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVI5, pp. 44–49. Blomley, R., Weinmann, M., Leitloff, J., Jutzi, B., 2014. Shape distribution features for
3: point cloud analysis – a geometric histogram approach on multiple scales. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences II-3, pp. 9–16. Boyko, A., Funkhouser, T., 2011. Extracting roads from dense point clouds in large
4: scale urban environment. ISPRS J. Photogr. Remote Sens. 66 (6), S02–S12. Breiman, L., 1996. Bagging predictors. Machine Learn. 24 (2), 123–140.
5: Breiman, L., 2001. Random forests. Machine Learn. 45 (1), 5–32.
6: Bremer, M., Wichmann, V., Rutzinger, M., 2013. Eigenvalue and graph-based object
7: extraction from mobile laser scanning point clouds. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences II-5/W2, pp. 55–60. Brodu, N., Lague, D., 2012. 3d terrestrial lidar data classification of complex natural
8: scenes using a multi-scale dimensionality criterion: applications in geomorphology. ISPRS J. Photogr. Remote Sens. 68, 121–134. Carlberg, M., Gao, P., Chen, G., Zakhor, A., 2009. Classifying urban landscape in aerial
9: lidar using 3d shape analysis. In: Proceedings of the IEEE International Conference on Image Processing, IEEE, Cairo, Egypt, 7–10 November, pp. 1701–1704. Chang, C.C., Lin, C.J., 2011. LIBSVM: a library for support vector machines. ACM
10: Trans. Intell. Syst. Technol. 2 (3), 27:1–27:27. Chehata, N., Guo, L., Mallet, C., 2009. Airborne lidar feature selection for urban
11: classification using random forests. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII3/W8, pp. 207–212. Cortes, C., Vapnik, V., 1995. Support-vector networks. Machine Learn. 20 (3), 273–
12: 297. Cover, T., Hart, P., 1967. Nearest neighbor pattern classification. IEEE Trans. Inform.
13: Theory 13 (1), 21–27. Criminisi, A., Shotton, J., 2013. Decision forests for computer vision and medical
14: image analysis. In: Advances in Computer Vision and Pattern Recognition. Springer, London, UK. Demantké, J., Mallet, C., David, N., Vallet, B., 2011. Dimensionality based scale
15: selection in 3d lidar point clouds. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII5/W12, pp. 97–102. Demantké, J., Vallet, B., Paparoditis, N., 2012. Streamed vertical rectangle detection
16: in terrestrial laser scans for facade database production. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences I-3, pp. 99– 104. Efron, B., 1979. Bootstrap methods: another look at the jackknife. Ann. Stat. 7 (1), 1–
17: 26. Fayyad, U.M., Irani, K.B., 1993. Multi-interval discretization of continuous-valued
18: attributes for classification learning. In: Proceedings of the International Joint Conference on Artificial Intelligence. Morgan Kaufman, Chambéry, France, 28 August - 3 September, pp. 1022–1027. Filin, S., Pfeifer, N., 2005. Neighborhood systems for airborne laser data. Photogr.
from
Arya, S., Mount, D.M., Netanyahu, N.S., Silverman, R., Wu, A.Y., 1998. An optimal
algorithm for approximate nearest neighbor searching in fixed dimensions. J.
ACM 45 (6), 891–923.
Belton, D., Lichti, D.D., 2006. Classification and segmentation of terrestrial laser
scanner point clouds using local variance information. International Archives of
the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVI-
5, pp. 44–49.
Blomley, R., Weinmann, M., Leitloff, J., Jutzi, B., 2014. Shape distribution features for
point cloud analysis – a geometric histogram approach on multiple scales. ISPRS
Annals of the Photogrammetry, Remote Sensing and Spatial Information
Sciences II-3, pp. 9–16.
Boyko, A., Funkhouser, T., 2011. Extracting roads from dense point clouds in large
scale urban environment. ISPRS J. Photogr. Remote Sens. 66 (6), S02–S12.
Breiman, L., 1996. Bagging predictors. Machine Learn. 24 (2), 123–140.
Breiman, L., 2001. Random forests. Machine Learn. 45 (1), 5–32.
Bremer, M., Wichmann, V., Rutzinger, M., 2013. Eigenvalue and graph-based object
extraction from mobile laser scanning point clouds. ISPRS Annals of the
Photogrammetry, Remote Sensing and Spatial Information Sciences II-5/W2, pp.
55–60.
Brodu, N., Lague, D., 2012. 3d terrestrial lidar data classification of complex natural
scenes using a multi-scale dimensionality criterion: applications in
geomorphology. ISPRS J. Photogr. Remote Sens. 68, 121–134.
Carlberg, M., Gao, P., Chen, G., Zakhor, A., 2009. Classifying urban landscape in aerial
lidar using 3d shape analysis. In: Proceedings of the IEEE International
Conference on Image Processing, IEEE, Cairo, Egypt, 7–10 November, pp.
1701–1704.
Chang, C.C., Lin, C.J., 2011. LIBSVM: a library for support vector machines. ACM
Trans. Intell. Syst. Technol. 2 (3), 27:1–27:27.
Chehata, N., Guo, L., Mallet, C., 2009. Airborne lidar feature selection for urban
classification using random forests. International Archives of the
Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII-
3/W8, pp. 207–212.
Cortes, C., Vapnik, V., 1995. Support-vector networks. Machine Learn. 20 (3), 273–
297.
Cover, T., Hart, P., 1967. Nearest neighbor pattern classification. IEEE Trans. Inform.
Theory 13 (1), 21–27.
Criminisi, A., Shotton, J., 2013. Decision forests for computer vision and medical
image analysis. In: Advances in Computer Vision and Pattern Recognition.
Springer, London, UK.
Demantké, J., Mallet, C., David, N., Vallet, B., 2011. Dimensionality based scale
selection in 3d lidar point clouds. International Archives of the
Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII-
5/W12, pp. 97–102.
Demantké, J., Vallet, B., Paparoditis, N., 2012. Streamed vertical rectangle detection
in terrestrial laser scans for facade database production. ISPRS Annals of the
Photogrammetry, Remote Sensing and Spatial Information Sciences I-3, pp. 99–
104.
Efron, B., 1979. Bootstrap methods: another look at the jackknife. Ann. Stat. 7 (1), 1–
26.
Fayyad, U.M., Irani, K.B., 1993. Multi-interval discretization of continuous-valued
attributes for classification learning. In: Proceedings of the International Joint
Conference on Artificial Intelligence. Morgan Kaufman, Chambéry, France, 28
August - 3 September, pp. 1022–1027.
Filin, S., Pfeifer, N., 2005. Neighborhood systems for airborne laser data. Photogr.
from