Aselsan Elektronik Sanayi Ve Ticaret Anonim Sirketi

Erkan Okuyan

Ozgur Yilmaz

Tolga Aksoy

Engin Uzun

Berk Ulker

Kadir Hakan Bicer

Murat Gevrekci

Cevdet Aykanat

A noise elimination method for detection applications to increase performance, robustness and efficiency is provided. The noise elimination method including the following steps of; initialization; candidate generation; obtain sensor data; obtain a transformation matrix; warping candidate signals into a Cumulative Signal Frame (CSF); get a next candidate; process a last candidate; query a set handler; add the candidate signals into the set handler; warp the candidate signals onto the CSF; add the candidate signals to the CSF at a warped position; process the CSF; interpret the CSF and generate target candidates; detect decisions and terminate.

Noise elimination method for detection applications

A method for optimizing focus of an optical system passively includes the following steps: discretizing optical positions with respect to precision requirements; initializing an idle counter to zero, going to the initial optical position, initializing a best position to current position, clearing a sharpness array; calculating correspondence; adding a sharpness value to a sharpness array; calculating a longest increasing subsequence on the sharpness array; checking if the longest increasing subsequence length increases; clearing the idle counter; setting the best position to the current position; incrementing the idle counter; checking if the termination threshold is reached; checking if the current position corresponds to the end of discrete optical positions if the termination threshold is not reached; driving motors to the next position; optionally improving the best position; going to the best position and terminating the method.

System and method for optimizing focus of optical system passively

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.

System and method for optimizing fiducial marker and camera positions/orientations

The present invention relates to the field of computation and covers methods to find one to one mapping between fiducial markers on a tracked object and fiducial marker projections on the image plane captured by a camera in optical object tracking systems. A method for solving correspondence problem is realized to find correspondences between 3D points of an object and 2D projection of that object onto the image plane so that this can be used to find the object's 3D location and orientation. It is designed to work without current pose of the tracked object thus it is equally efficient on initial correspondence problem as correspondence problem. Furthermore, a method for selecting LED groups to be used for solving correspondence problem is also presented, which uses pose data representing possible poses of tracked object under working conditions thus LEDS groups are selected to satisfy use case requirements.

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Ankara, Turkey

Erkan Okuyan