We propose a method for object recognition in an unconstrained condition. This includes wide range of illumination, unknown view points and complicated background. We simplified the general problem by placing special design patterns (Tsai's (1987) camera calibration chart) on the object that allows us to solve the pose determination problem easily. After establishing the methodological framework, we experiment with this technique on a wide range of real data to show the reliability of the approach. We argue that with this capability we should be able to (a) establish camera position with respect to a landmark, (b) recognise an object which is tagged with the calibration chart and (c) test any camera calibration and 3D pose estimation routines, thus facilitating future research and applications in mobile robots navigation, 3D reconstruction and stereo vision.
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