| dc.description.abstract | Setting up large multi-projector arrays today usually come at a cost; manual calibration of each projector requires time. The orientation of the image from each projector must be correctly aligned in six axes to make the final projected output fit the screen. Not all aspects of calibrating projectors are possible to correct, consumer hardware usually only covers two or three of the axes, the remainder are often corrected using clever projector placement. Also, the degree of which it is possible to adjust is also limited, decreasing placement flexibility. As the collaboration surfaces in Hems lab requires a large number of projectors to work seamlessly together, good calibration techniques are required in order to keep setup and maintenance time low, while giving highly accurate calibration results. Abstract By creating a software demonstrator that automates much of the calibration and enables quick and easy setup, I have made possible rapid prototyping, testing and demonstration of multi-projector arrays, both with single and stereoscopic views. As I will prove, this software shows a flexible approach that may be of use, not only to the Caruso lab and future Hems lab, but may also be used in other settings where projector technology up to this date still has not been widely used, by overcoming the calibration and image warping hurdles and limitations. Abstract The software is developed with basis in the OpenCV computer vision library, and implemented in Python. Tests show that calibration time for a single projector may be cut down to a matter of seconds, regardless of the placement of the projector in relation to the screen, whereas traditional calibration often still not reach the same level of accuracy even if taking tens of minutes or require repositioning of the projector to compensate for the lack of adjustment possibilities. | nb_NO |
