In this paper we consider the problem of finding the position of a point in space given its projections in multiple images taken by cameras with known calibration and pose. Ideally the 3D point can be obtained as the intersection of multiple known rays in space. However, with noise the rays do not meet at a single point generally. Therefore, it is necessary to find a best point of intersection. In this paper we propose a modification of the method (Ma et al., 2001. Journal of Communications in Information and Systems, (1):51-73) based on the multiple-view epipolar constraints. The solution is simple in concept and straightforward to implement. It includes generally two steps: first, image points are corrected through approximating the error model to the first order, and then the 3D point can be reconstructed from the corrected image points using any generic triangulation method. Experiments are conducted both on simulated data and on real data to test the proposed method against previous methods. It is shown that results obtained with the proposed method are consistently more accurate than those of other linear methods. When the measurement error of image points is relatively small, its results are comparable to those of maximum likelihood estimation using Newton-type optimizers; and when processing image-point correspondences cross a small number of views, the proposed method is by far more efficient than the Newton-type optimizers.

Abstract-Event data from proton-proton collisions at the LHC will be selected by the ATLAS experiment in a three level trigger system, which reduces the initial bunch crossing rate of 40 MHz at its first two trigger levels (LVL1+LVL2) to ∼ 3 kHz. At this rate the Event-Builder collects the data from all Read-Out system PCs (ROSs) and provides fully assembled events to the the EventFilter (EF), which is the third level trigger, to achieve a further rate reduction to ∼ 200 Hz for permanent storage. The EventBuilder is based on a farm of O(100) PCs, interconnected via Gigabit Ethernet to O(150) ROSs. These PCs run Linux and multi-threaded software applications implemented in C++. All the ROSs and one third of the Event-Builder PCs are already installed and commissioned. We report on performance tests on this initial system, which show promising results to reach the final data throughput required for the ATLAS experiment.

Abstract-The base-line design and implementation of the ATLAS DAQ DataFlow system is described. The main components of the DataFlow system, their interactions, bandwidths, and rates are discussed and performance measurements on a 10% scale prototype for the final ATLAS TDAQ DataFlow system are presented. This prototype is a combination of custom design components and of multithreaded software applications implemented in C++ and running in a Linux environment on commercially available PCs interconnected by a fully switched gigabit Ethernet network.

Abstract-Event data from proton-proton collisions at the LHC will be selected by the ATLAS experiment in a three level trigger system, which reduces the initial bunch crossing rate of 40 MHz at its first two trigger levels (LVL1+LVL2) to ∼ 3 kHz. At this rate the Event-Builder collects the data from all Read-Out system PCs (ROSs) and provides fully assembled events to the the EventFilter (EF), which is the third level trigger, to achieve a further rate reduction to ∼ 200 Hz for permanent storage. The EventBuilder is based on a farm of O(100) PCs, interconnected via Gigabit Ethernet to O(150) ROSs. These PCs run Linux and multi-threaded software applications implemented in C++. All the ROSs and one third of the Event-Builder PCs are already installed and commissioned. We report on performance tests on this initial system, which show promising results to reach the final data throughput required for the ATLAS experiment.

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