Stephan Ihrke's research while affiliated with Fraunhofer Institute for Transportation and Infrastructure Systems IVI and other places

Publications (5)

Chapter
Full-text available
We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the object in known 6D poses. The benchmark comprises of: (i) eight datasets in a unified format that cover different practical scenarios, including two new datasets focusing on...
Preprint
Full-text available
We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the object in known 6D poses. The benchmark comprises of: i) eight datasets in a unified format that cover different practical scenarios, including two new datasets focusing on...
Conference Paper
Ubiquitous projection or "display everywhere" is a popular paradigm, according to which regular rooms are augmented with projected digital content in order to create immersive interactive environments. In this work, we revisit this concept, where instead of considering every physical surface and object as a display, we seek to determine areas that...
Conference Paper
Full-text available
This work investigates the problem of 6-Degrees-Of-Freedom (6-DOF) object tracking from RGB-D images, where the object is rigid and a 3D model of the object is known. As in many previous works, we utilize a Particle Filter (PF) framework. In order to have a fast tracker, the key aspect is to design a clever proposal distribution which works reliabl...

Citations

... The 6D poses are estimated from the predicted many-to-many 2D-3D correspondences by a RANSAC-based robust fitting procedure. In the BOP Challenge 2019 [100,106], the method outperformed all RGB and most RGB-D and D methods on the T-LESS [102], YCB-V [271], and LM-O [17] datasets. ...
... Post-Post-it [34], Maps Around Me [52], Small Multiples [38], Immersive Space to Think [36], VR Memory Palace [69] Spatial Analytic Interfaces [19], HoloDoc [35], Smart Projection [45], SnapToReality [47], Space-Adaptive Augmentation [56], ARphy [12] CollaboVR [25], Share Surfaces and Spaces [33] Collaboration ...
... Besides single frame pose estimation, many recent works focus on the temporal tracking of object poses. Instance-level object pose tracking approaches include optimization [66,81,106,85], filtering [96,15,46,41,16], and direct regression of inter-frame pose change [94]. Recent works on categorylevel object pose tracking can emerge category-level keypoints [88] without known CAD model in testing, refining coarse pose from keypoint registration by pose graph optimization [93], and learning inter-frame pose change from canonicalized point clouds [95]. ...