Sagi Filin

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This paper presents an algorithm for the extraction of surface clusters from airborne laser data. Surface structure analysis is fundamental to almost any application involving LIDAR data, yet most algorithms focus only on identifying planar segments. The proposed algorithm is more general insofar as it aims at extracting surface segments that exhibit an(More)
The paper concerns the generalization of DTM extracted from LiDAR data. The essence of generalization is reducing details while enhancing important features at the same time; so for the purpose of terrain surface visualization special attention has to be given to the enhancement and generalization of topographic objects like dams, roads etc. The focus of(More)
  • Bea Csathó, Toni Schenk, Dong-Cheon Lee, Sagi Filin
  • 1999
In this paper, we describe how object recognition benefits from exploiting multispectral and multisensor datasets. After a brief introduction we summarize the most important principles of object recognition and multisensor fusion. This serves as the basis for the proposed architecture of a multisensor object recognition system. It is characterized by(More)
Knowledge provided by GIS data can alleviate many problems associated with object recognition from aerial imagery. However, as the scale of the GIS increases (for example a GIS database of topographic maps) positional disagreements between the data sets hamper the efficient utilization of this data. Presented here is a novel approach to the registration of(More)
Measurements with airborne laser scanners are performed in strips, usually with multiple length strips and a few cross strips. Due to i) wrong or inaccurate calibration of the entire measurement system and due to ii) the limited accuracy of the exterior orientation determination with GPS and IMU and systematic errors of these devices, adjacent strips can(More)
Terrestrial laser scanning is becoming a standard for 3D modeling of complex scenes. Results of the scan contain detailed geometric information about the scene; however, the lack of semantic details is still a gap in making this data useable for mapping. In this paper we propose a framework for object recognition in laser scans. The 3D point cloud, which is(More)
We present in this paper an algorithm for the detection of changes based on terrestrial laser scanning data. Detection of changes has been a subject for research for many years, seeing applications such as motion tracking, inventory-like comparison and deformation analysis as only a few examples. One of the more difficult tasks in the detection of changes(More)