For deploying any robotic solution, the most cumbersome yet essential task remains calibration. Almost every robotic system uses a camera to extract information to produce some output. In the case of the pick-and-place system, camera information is used to detect objects and estimate their position in real-world space. The accuracy of tasks like sorting and stacking the objects in the box depends on their estimated pose in the space, especially when they need to be arranged in a confined space. We propose the automatic calibration of the workspace using distinct markers. Our experimentation was carried out with loose packets of recycled paper, which consists of small parts inside. We evaluate our results on the basis of translation errors of the estimated centroid position of objects with respect to the position given by the calibrated 3D camera. In conclusion, we also assess the typical pick-and-place performance on the success rate of stacking the packets in a small box.