The depth information of RGB-D sensors has greatly simplified some common challenges in
computer vision and enabled breakthroughs for several tasks. In this paper, we propose to …

This paper addresses the problem of recognizing free-form 3D objects in point clouds.
Compared to traditional approaches based on point descriptors, which depend on local …

Point cloud registration sits at the core of many important and challenging 3D perception
problems including autonomous navigation, SLAM, object/scene recognition, and …

A computer-implemented method for estimating a pose of an articulated object model that is
a computer based 3D model of a real world object observed by one or more source …

We present an object pose estimation approach exploiting both geometric depth and
photometric color information available from an RGB-D sensor. In contrast to various efforts …

Quantification of uncertainty in point cloud matching is critical in many tasks such as pose
estimation, sensor fusion, and grasping. Iterative closest point (ICP) is a commonly used …

Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water
turbidity, provide promising opportunities for perception and object recognition in …

Registration is the problem of bringing together two or more 3D shapes, either of the same
object or of two different but similar objects. This chapter first introduces the classical …

Point cloud registration sits at the core of many important and challenging 3D perception
problems including autonomous navigation, SLAM, object/scene recognition, and …

Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water
turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in …