Many Robotics and Augmented Reality applications require to accurately estimate 3D poses. We build 3D object tracking frameworks based on the detection and pose estimation of discriminative parts of the target object. These work in typical AR scenes with poorly textured objects, under heavy occlusions, drastic light changes, and changing background.
3D Robust Part-based Object Tracking
Tracking occluded, cluttered objects with partsMany Robotics and Augmented Reality applications require to to accurately estimate 3D poses of poorly textured, highly occluded objects.More in particular, we are interested in scenes with poorly textured objects, possibly visible only under heavy occlusions, drastic light changes, and changing background. A depth sensor is not an option in our setup, as (…)
Robust 3D Tracking with Descriptor Fields
3D Tracking in extreme environmentsReliable 3D tracking of poorly textured, specular objects is a very challenging task. This is a clear obstacle to the development of Robotics and Augmented Reality applications in industrial environments, where such objects can typically be found.Our approach allows to register input frames captured by a standard, low-quality monocular camera in (…)