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LSD-SLAM: Large-Scale Direct Monocular SLAM
TLDR
A novel direct tracking method which operates on \(\mathfrak{sim}(3)\), thereby explicitly detecting scale-drift, and an elegant probabilistic solution to include the effect of noisy depth values into tracking are introduced.
A Multi-view Stereo Benchmark with High-Resolution Images and Multi-camera Videos
TLDR
This benchmark is the first to cover the important use case of hand-held mobile devices while also providing high-resolution DSLR camera images and provides data at significantly higher temporal and spatial resolution.
BAD SLAM: Bundle Adjusted Direct RGB-D SLAM
TLDR
A novel, fast direct BA formulation is presented which is implemented in a real-time dense RGB-D SLAM algorithm, and the proposed algorithm outperforms all other evaluated SLAM methods.
Semi-dense visual odometry for AR on a smartphone
TLDR
It is shown how a simple world model for AR applications can be derived from semi-dense depth maps, and the practical applicability in the context of an AR application in which simulated objects can collide with real geometry is demonstrated.
3D Modeling on the Go: Interactive 3D Reconstruction of Large-Scale Scenes on Mobile Devices
This paper presents a system for 3D reconstruction of large-scale outdoor scenes based on monocular motion stereo. Ours is the first such system to run at interactive frame rates on a mobile device
Supplementary Material for A MultiView Stereo Benchmark with High-Resolution Images and Multi-Camera Videos
TLDR
The initial scenes in this benchmark consist of 7 outdoor and 7 indoor scenes that contain thin structures such as the trees in forest, or a rope in playground, and several scenes also contain large homogeneous or reflective surfaces that make the scenes challenging for stereo algorithms.
Illumination change robustness in direct visual SLAM
TLDR
This paper determines their accuracy and robustness in the context of odometry and of loop closures, both on real images as well as synthetic datasets with simulated lighting changes, and finds that for real images, a Census-based method outperforms the others.
Real-Time View Correction for Mobile Devices
TLDR
A real-time method for rendering novel virtual camera views from given RGB-D (color and depth) data of a different viewpoint efficiently inpainted in a temporally consistent way.
SurfelMeshing: Online Surfel-Based Mesh Reconstruction
TLDR
This novel approach enables to maintain a dense surface representation of the scene during SLAM which can quickly adapt to loop closures and asynchronously remeshing the surface where necessary, and can reconstruct thin objects since objects do not need to enclose a volume.
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