• Publications
  • Influence
KinectFusion: Real-time dense surface mapping and tracking
We present a system for accurate real-time mapping of complex and arbitrary indoor scenes in variable lighting conditions, using only a moving low-cost depth camera and commodity graphics hardware.
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera
Novel extensions to the core GPU pipeline demonstrate object segmentation and user interaction directly in front of the sensor, without degrading camera tracking or reconstruction, to enable real-time multi-touch interactions anywhere.
Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images
We address the problem of inferring the pose of an RGB-D camera relative to a known 3D scene, given only a single acquired image. Our approach employs a regression forest that is capable of inferring
SenseCam: A Retrospective Memory Aid
The results of this initial evaluation of the SenseCam are extremely promising; periodic review of images of events recorded by SenseCam results in significant recall of those events by the patient, which was previously impossible.
Real-time 3D reconstruction at scale using voxel hashing
An online system for large and fine scale volumetric reconstruction based on a memory and speed efficient data structure that compresses space, and allows for real-time access and updates of implicit surface data, without the need for a regular or hierarchical grid data structure.
BundleFusion: real-time globally consistent 3D reconstruction using on-the-fly surface re-integration
This work systematically addresses issues with a novel, real-time, end-to-end reconstruction framework, which outperforms state-of-the-art online systems with quality on par to offline methods, but with unprecedented speed and scan completeness.
Real-Time 3D Reconstruction in Dynamic Scenes Using Point-Based Fusion
A new system for real-time dense reconstruction with equivalent quality to existing online methods, but with support for additional spatial scale and robustness in dynamic scenes, designed around a simple and flat point-Based representation.
StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction
This paper presents StereoNet, the first end-to-end deep architecture for real-time stereo matching that runs at 60fps on an NVidia Titan X, producing high-quality, edge-preserved, quantization-free
Modeling Kinect Sensor Noise for Improved 3D Reconstruction and Tracking
The derived noise model can be used to filter Kinect depth maps for a variety of applications and applies to the KinectFusion system to extend filtering, volumetric fusion, and pose estimation within the pipeline.
Fusion4D: real-time performance capture of challenging scenes
This work contributes a new pipeline for live multi-view performance capture, generating temporally coherent high-quality reconstructions in real-time, highly robust to both large frame-to-frame motion and topology changes, allowing us to reconstruct extremely challenging scenes.