  This work presents a flexible system to reconstruct 3D models of objects
captured with an RGB-D sensor. A major advantage of the method is that our
reconstruction pipeline allows the user to acquire a full 3D model of the
object. This is achieved by acquiring several partial 3D models in different
sessions that are automatically merged together to reconstruct a full model. In
addition, the 3D models acquired by our system can be directly used by
state-of-the-art object instance recognition and object tracking modules,
providing object-perception capabilities for different applications, such as
human-object interaction analysis or robot grasping. The system does not impose
constraints in the appearance of objects (textured, untextured) nor in the
modelling setup (moving camera with static object or a turn-table setup). The
proposed reconstruction system has been used to model a large number of objects
resulting in metrically accurate and visually appealing 3D models.
