Navigation systems help users access unfamiliar environments. Current technological
advancements enable users to encapsulate these systems in handheld devices, which …

Abstract 3D object recognition and pattern recognition are active and fast-growing research
areas in the field of computer vision. It is mandatory to define the pattern class, feature …

We present an approach for 3D global human mesh recovery from monocular videos
recorded with dynamic cameras. Our approach is robust to severe and long-term occlusions …

Capturing the interactions between humans and their environment in 3D is important for
many applications in robotics, graphics, and vision. Recent works to reconstruct the 3D …

We introduce the Imperial College London and National University of Ireland Maynooth (ICL-
NUIM) dataset for the evaluation of visual odometry, 3D reconstruction and SLAM algorithms …

In this paper, we present a novel benchmark for the evaluation of RGB-D SLAM systems. We
recorded a large set of image sequences from a Microsoft Kinect with highly accurate and …

Today, visual recognition systems are still rarely employed in robotics applications. Perhaps
one of the main reasons for this is the lack of demanding benchmarks that mimic such …

Visual SLAM (simultaneous localization and mapping) refers to the problem of using
images, as the only source of external information, in order to establish the position of a …

3D object recognition in cluttered scenes is a rapidly growing research area. Based on the
used types of features, 3D object recognition methods can broadly be divided into two …

We present an approach to simultaneous localization and mapping (SLAM) for RGB-D
cameras like the Microsoft Kinect. Our system concurrently estimates the trajectory of a hand …