A supervised approach for object extraction from terrestrial laser point clouds demonstrated on trees

PIA 2007 - Photogrammetric Image Analysis, Proceedings

Volumn , Issue , 2007, Pages 135-140

  Barnea, Shahar ^a   Filin, Sagi ^a   Alchanatis, Victor ^b  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

^b EXTENSION SERVICE   (Israel)

Author keywords

Algorithms; Feature extraction; Object recognition; Point cloud; Terrestrial laser scanner

Indexed keywords

COMPLEX DATA STRUCTURES; FEATURE SPACE ANALYSIS; LOW LEVEL IMAGE PROCESSING; NATURAL REPRESENTATION; NEIGHBORHOOD STRUCTURE; POINT CLOUD; TERRESTRIAL LASER SCANNERS; TERRESTRIAL LASER SCANNING;

ALGORITHMS; FEATURE EXTRACTION; FORESTRY; IMAGE ANALYSIS; OBJECT RECOGNITION; PHOTOGRAMMETRY; SEMANTICS; THREE DIMENSIONAL;

TREES (MATHEMATICS);

EID: 79952391165     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Arya, S., Mount D. M., Netanyahu N. S., Silverman R., Wu A., 1998. An optimal algorithm for approximate nearest neighbor searching. Journal of the ACM, 45, 891-923.
2. Bienert, A., Maas, H.-G., Scheller, S. (2006). Analysis of The Information Content of Terrestrial Laserscanner Point Clouds For The Automatic Determination Of Forest Inventory Parameters. Workshop on 3D Remote Sensing in Forestry, 14th-15th Feb 2006, Vienna.
3. Comaniciu D., Meer. P., 2002. Mean shift: A robust approach toward feature space analysis. IEEE trans. PAMI, 24:603-19.
4. nd ed. Wiley, 2000.
5. Ford, L., Fulkerson, D., (1962). Flows in Networks Princeton Univ. Press.
6. Frome A., Huber, R. Kolluri, T. Buelow, and J. Malik (2004). Recognizing Objects in Range Data Using Regional Point Descriptors. in Proc of ECCV 2004, 3, 224-237.
7. Huber, D., Kapuria, A., Donamukkala, R., Hebert, M. (2004) Parts-Based 3D Object Recognition. Proc. IEEE Int'l Conf. Computer Vision and Pattern Recognition, vol. 2, 82-89.
8. Huber D. and Hebert, M., (2003). Fully automatic registration of multiple 3D data sets. Image and Vision Computation 21(7):637-650.
9. Mian, A., Bennamoun, M., Owens, R., (2006). Three-Dimensional Model-Based Object Recognition and Segmentation in Cluttered Scenes. IEEE transactions on PAMI. 28(10), 1584-1601.
10. Pechuk M., Soldea O., Rivlin E., (2005) Function based classification from 3D Data via Generic and Symbolic Models. In AAAI, 950-955.
11. Rabanni T., 2006. Automatic reconstruction of Industrial Installations using point clouds and images. PhD thesis. NCG, publication on Geodesy 62.
12. Russell, C. B., Efros A., Sivic J., Freeman T. W., Zisserman A., (2006). Using Multiple Segmentations to Discover Objects and their Extent in Image Collections. in Proc. of CVPR 2006 2, 1605-1614.