SYSTEM CALIBRATION OF INTELLIGENT PHOTOGRAMMETRON

Abstract

Photogrammetron represents a class of intelligent photogrammetric systems aiming at realizing a number of newly defined functionalities of intelligent photogrammetry that go beyond the traditional photogrammetry and the currently dominant digital one, including real-time photogrammetry in video surveillance, photogrammetry-enabled robots, intelligent multi-camera network for close-range photogrammetry. This paper addresses the geometric calibration of Photogrammetron I - the first type of Photogrammetron which is designed to be a coherent stereo photogrammetric system in which two cameras are mounted on a physical base but driven by an intelligent agent architecture. The system calibration is divided into two parts: the in-lab calibration determines the fixed parameters in advance of system operation, and the in-situ calibration keeps tracking the free parameters in realtime during system operation. In a video surveillance setup, prepared control points are tracked in stereo image sequences, so that the free parameters of the system can be continuously updated through iterative bundle adjustment and Karlman filtering. Two methods of calibration are distinguished: the strong stereo mode where a minimal set of parameters are tracked, and the weak stereo model where each camera is calibrated independently through tracking control points.