Consumer-grade digital cameras suffer from geometrical instability that may cause problems when used in photogrammetric applications. This paper provides a comprehensive review of this issue of interior orientation parameter variation over time, it explains the common ways used for coping with the issue, and describes the existing methods for performing stability analysis for a single camera. The paper then points out the lack of coverage of stability analysis for multi-camera systems, suggests a modification of the collinearity model to be used for the calibration of an entire photogrammetric system, and proposes three methods for system stability analysis. The proposed methods explore the impact of the changes in interior orientation and relative orientation/mounting parameters on the reconstruction process. Rather than relying on ground truth in real datasets to check the system calibration stability, the proposed methods are simulation-based. Experiment results are shown, where a multi-camera photogrammetric system was calibrated three times, and stability analysis was performed on the system calibration parameters from the three sessions. The proposed simulation-based methods provided results that were compatible with a real-data based approach for evaluating the impact of changes in the system calibration parameters on the three-dimensional reconstruction.

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(zlari, ahabib, ekwak@ucalgary.ca) Commission V, WG V/3 KEY WORDS: Segmentation, Kd-tree data structure, Adaptive cylinder neighbourhood, Clustering attributes, Octree space partitioning ABSTRACT:Automatic processing and object extraction from 3D laser point cloud is one of the major research topics in the field of photogrammetry. Segmentation is an essential step in the processing of laser point cloud, and the quality of extracted objects from laser data is highly dependent on the validity of the segmentation results. This paper presents a new approach for reliable and efficient segmentation of planar patches from a 3D laser point cloud. In this method, the neighbourhood of each point is firstly established using an adaptive cylinder while considering the local point density and surface trend. This neighbourhood definition has a major effect on the computational accuracy of the segmentation attributes. In order to efficiently cluster planar surfaces and prevent introducing ambiguities, the coordinates of the origin's projection on each point's best fitted plane are used as the clustering attributes. Then, an octree space partitioning method is utilized to detect and extract peaks from the attribute space. Each detected peak represents a specific cluster of points which are located on a distinct planar surface in the object space. Experimental results show the potential and feasibility of applying this method for segmentation of both airborne and terrestrial laser data.

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ABSTRACT:The registration process of terrestrial laser scans (TLS) targets the problem of how to combine several laser scans in order to attain better information about features than what could be obtained through single scan. The main goal of the registration process is to estimate the parameters which determine geometrical variation between the origins of datasets collected from different locations. Scale, shifts, and rotation parameters are usually used to describe such variation. This paper presents a framework for the registration of overlapping terrestrial laser scans by establishing an automatic matching strategy that uses 3D linear features. More specifically, invariant separation characteristics between 3D linear features extracted from laser scans will be used to establish hypothesized conjugate linear features between the laser scans. These candidate matches are then used to geo-reference scans relative to a common reference frame. The registration workflow simulates the well-known RANndom Sample Consensus method (RANSAC) for determining the registration parameters, whereas the iterative closest projected point (ICPP) is utilized to determine the most probable solution of the transformation parameters from several solutions. The experimental results prove that the proposed methodology can be used for the automatic registration of terrestrial laser scans using linear features.