Abstract: A system including a camera configured to capture a first image of an offshore structure and a second image of the offshore structure, and a processor coupled to the camera, the processor configured to receive the first image and the second image from the camera, recognize a first visual pattern in the first image and the second image, extract pixel coordinates associated with a first position of the first visual pattern in the first image and a second position of the first visual pattern in the second image, and determine a first distance between the first position and the second position, or the first position of the first visual pattern and a first position of a second visual pattern fixably attached to the offshore structure in the first image.

Abstract: A method does not use high resource and high power consuming memory elements (LUT, Block RAM, etc.) or a distributed RAM in an implementation of nonlinear activation functions of artificial neural networks (ANN), eliminating a need for multiplication elements completely by using shift operations. Since each neuron includes an activation function, eliminating a multiplication element saves significant amount of resource and power in an implementation of the ANN.

Abstract: A system including a camera configured to capture a first image of an offshore structure and a second image of the offshore structure, and a processor coupled to the camera, the processor configured to receive the first image and the second image from the camera, recognize a first visual pattern in the first image and the second image, extract pixel coordinates associated with a first position of the first visual pattern in the first image and a second position of the first visual pattern in the second image, and determine a first distance between the first position and the second position, or the first position of the first visual pattern and a first position of a second visual pattern fixably attached to the offshore structure in the first image.

Abstract: The invention relates to a quantized detection in uplink mimo with oversampling that is a temporal oversampling in quantized uplink MIMO systems.

Abstract: Recurrent neural networks are powerful tools for handling incomplete data problems in machine learning thanks to their significant generative capabilities. However, the computational demand for algorithms to work in real time applications requires specialized hardware and software solutions. We disclose a method for adding recurrent processing capabilities into a feedforward network without sacrificing much from computational efficiency. We assume a mixture model and generate samples of the last hidden layer according to the class decisions of the output layer, modify the hidden layer activity using the samples, and propagate to lower layers. For an incomplete data problem, the iterative procedure emulates feedforward-feedback loop, filling-in the missing hidden layer activity with meaningful representations.

Abstract: The present invention relates to a simple and effective system and method for measuring camera based tracker system accuracy, especially for a helmet-mounted tracker system, utilizing Coordinate Measuring Machine (CMM). The method comprises the steps of; computing spatial relation between tracked object and calibration pattern using CMM; computing relation between reference camera and tracker camera; computing relation between reference camera and calibration pattern; computing ground truth relation between tracker camera and tracked object; obtaining actual tracker system results; comparing these results with the ground truth relations and finding accuracy of the tracker system; recording accuracy results; testing if the accuracy results is a new calculation required. The system comprises; a reference camera; a calibration pattern visible by reference camera; a camera spatial relation computation unit; a relative spatial relation computation unit a memory unit; a spatial relation comparison unit.

Abstract: A method for optimizing fiducial marker and camera positions/orientations is realized to simulate camera and fiducial positions and pose estimation algorithm to find best possible marker/camera placement comprises the steps of: acquiring mesh data representing possible camera positions and feasible orientation boundaries of cameras on the environment of tracked object; acquiring mesh data representing possible active marker positions and feasible orientation placements of markers on a tracked object; pose data representing possible poses of tracked object under working conditions; initializing the control parameter for camera placement; create initial solution strings for camera placement; solving marker placement problem for the current camera placement; evaluating the quality of the current LED and camera placement taking pose coverage, pose accuracy, number of placed markers, number of placed camera etc. into account; determining if a stopping criterion is satisfied.

Abstract: The present invention relates to the field of computation and simulation and covers methods to optimize the fiducial marker positions in optical object tracking systems, by simulating the visibility.

Abstract: Recurrent neural networks are powerful tools for handling incomplete data problems in machine learning thanks to their significant generative capabilities. However, the computational demand for algorithms to work in real time applications requires specialized hardware and software solutions. We disclose a method for adding recurrent processing capabilities into a feedforward network without sacrificing much from computational efficiency. We assume a mixture model and generate samples of the last hidden layer according to the class decisions of the output layer, modify the hidden layer activity using the samples, and propagate to lower layers. For an incomplete data problem, the iterative procedure emulates feedforward-feedback loop, filling-in the missing hidden layer activity with meaningful representations.

Abstract: The present invention relates to a method for object tracking where the tracking is realized based on object classes, where the classifiers of the objects are trainable without a need for supervision and where the tracking errors are reduced and robustness is increased.

Abstract: A method for optimizing fiducial marker and camera positions/orientations is realized to simulate camera and fiducial positions and pose estimation algorithm to find best possible marker/camera placement comprises the steps of: acquiring mesh data representing possible camera positions and feasible orientation boundaries of cameras on the environment of tracked object; acquiring mesh data representing possible active marker positions and feasible orientation placements of markers on a tracked object; pose data representing possible poses of tracked object under working conditions; initializing the control parameter for camera placement; create initial solution strings for camera placement; solving marker placement problem for the current camera placement; evaluating the quality of the current LED and camera placement taking pose coverage, pose accuracy, number of placed markers, number of placed camera etc. into account; determining if a stopping criterion is satisfied.

Abstract: The present invention relates to a simple and effective system and method for measuring camera based tracker system accuracy, especially for a helmet-mounted tracker system, utilizing Coordinate Measuring Machine (CMM). The method comprises the steps of; computing spatial relation between tracked object and calibration pattern using CMM; computing relation between reference camera and tracker camera; computing relation between reference camera and calibration pattern; computing ground truth relation between tracker camera and tracked object; obtaining actual tracker system results; comparing these results with the ground truth relations and finding accuracy of the tracker system; recording accuracy results; testing if the accuracy results is a new calculation required. The system comprises; a reference camera; a calibration pattern visible by reference camera; a camera spatial relation computation unit; a relative spatial relation computation unit a memory unit; a spatial relation comparison unit.

Abstract: The present invention relates to the field of computation and simulation and covers methods to optimize the fiducial marker positions in optical object tracking systems, by simulating the visibility.

Abstract: A method and system for blind channel estimation comprises acquiring two mixtures of at least one at least weakly W-disjoint orthogonal source signal, calculating point-by-point ratios of a transform of a time-window of each of said mixture signals, determining channel parameter estimates from said ratios, constructing a histogram of said channel parameter estimates, repeating the calculating, determining and constructing steps for successive time windows of the mixture signals, and selecting as estimates of said channel parameters those estimates associated with identified peaks on said histogram.