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In the current test setup we are using the current scene. Each correspondence provides one object a standard video beamer and a standard digital camera, but we point by triangulating between the projector and the camera. The special requirements of this miniaturized system will be explained The test setup uses a standard video beamer projecting only as well as our implementation.
Our approach reduces hardware one white noise pattern.
Later on this projector will be substi- complexity to a minimum using only one calibrated camera and tuted by a simpler device using a low-cost gobo known from one calibrated fixed pattern projector.
The scene is ob- In this paper we present the whole system also including the served by a standard digital camera. The focus will be on the hardware setup, Figure 1 shows the workflow we intend to realize using this but we also give an introduction to the software methods used. In this paper we want to present a new approach using a one-shot acquisition system, that can easily be miniaturized. Furthermore a 3D registration on-the- fly can be realized using this system.
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The system is imple- mented using a fixed pattern projection-based scan mecha- nism, a fast online registration and a fast visualization of the resulting 3D data. Perhaps the most famous results of such an approach were published by Rusinkiewicz et al. These researchers used a multi-pattern projection system with a com- plex image-to-image stripe tracking mechanism.
Due to the need of projecting various patterns over time this system lacks Fig.
Head: Prof. For details re- garding GraspIt! Normally projector calibration is done using a well-known extended DLT algorithm which is used for camera calibration pattern [1,8].
Our aim was to calibrate the pattern projector figure 2. This image will serve as a template for the whole following Section III shows the test-bed hardware and the software envi- process.
In the second step the pattern is projected onto planes ronment. Now the same correlation algorithm which will be utilized during the scan process later on except neglecting the epipolar II.
For each A.
Camera and Projector Calibration 2D-correspondence that is found the related 3D-points are The scan system is calibrated in two steps. In the first step calculated by using the parameters of the calibrated camera the camera is calibrated, which is then used for calibrating the and intersecting the resulting camera rays with the well-known projector in the second step.
Figure 2 shows the intersec- tive procedure in order to calculate the optimal set of parame- tions of the camera rays with the projector rays illustrating the ters.
In each iteration the DLT parameters are calculated first, cooperation of the camera and the pattern projector. Thereby, an object point is are calculated using a least squares approach. We acquire this set using a stack of acrylic point in the template image is calculated in the same way. Using the parameters of the calibrated projector one can now determine the projector ray g3 easily by inserting the coordinates n and m.
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Finally the object point is defined by the intersection of the straight lines g1 and g3. If no intersection can be found the closest point between g1 and g3 is used for the further calcula- tions.
Correlation Techniques To retrieve local patterns in the camera image one has to calculate the correlation beween camera image and template image.
We first tried an implementation of the Least Squares Correlation algorithm LSC, [2,4,15] which works well and which is even capable of dealing with perspective distortions but takes too much calculation time and therefore cannot be used in this real-time system.
As a result the current system uses a standard Sum of Squared Differences correlation technique SSD, [13,16] which can be implemented considerably faster and which de- Fig. Projector calibration is done utilizing the same i,j T in the template image, the SSD correlation algorithm searches for the displacement vector d1,d2 T that minimizes era which is connected to a standard BTbased frame grab- the following error measure c d1,d2 [13,15,16]: ber.
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This item will be shipped through the Global Shipping Program and includes international tracking. You can download our educational brochure on how to spot counterfeiting and the very latest list of counterfeited parts from Brokerlynx. However, a handful of other advancements have taken place. As a conclusion we want to mention that the strategy is to permit even bad matches as the result of the search for a pre- condition, since a bad match can be justified by perspective distortions at this stage.
Now the same correlation algorithm which will be utilized during the scan process later on except neglecting the epipolar II.
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