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Proceedings ArticleDOI

KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera

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TLDR
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.
Abstract
KinectFusion enables a user holding and moving a standard Kinect camera to rapidly create detailed 3D reconstructions of an indoor scene. Only the depth data from Kinect is used to track the 3D pose of the sensor and reconstruct, geometrically precise, 3D models of the physical scene in real-time. The capabilities of KinectFusion, as well as the novel GPU-based pipeline are described in full. Uses of the core system for low-cost handheld scanning, and geometry-aware augmented reality and physics-based interactions are shown. 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. These extensions are used to enable real-time multi-touch interactions anywhere, allowing any planar or non-planar reconstructed physical surface to be appropriated for touch.

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Proceedings ArticleDOI

DuploTrack: a real-time system for authoring and guiding duplo block assembly

TL;DR: A realtime system which infers and tracks the assembly process of a snap-together block model using a Kinect® sensor and proposes a novel way of assembly guidance where the next block to be added is rendered in blinking mode with the tracked virtual model on screen.
Proceedings ArticleDOI

Practical Human Sensing in the Light

TL;DR: StarLight is an infrastructure-based sensing system that reuses light emitted from ceiling LED panels to reconstruct fine-grained user skeleton postures continuously in real time, with neither invasive cameras nor on-body sensors.
Book ChapterDOI

Learning Shape Priors for Single-View 3D Completion and Reconstruction

TL;DR: In this article, the authors propose ShapeHD, which integrates deep generative models with adversarially learned shape priors, which serve as a regularizer, penalizing the model only if its output is unrealistic, not if it deviates from the ground truth.
Journal ArticleDOI

High-Quality Depth Map Upsampling and Completion for RGB-D Cameras

TL;DR: This paper describes an application framework to perform high-quality upsampling and completion on noisy depth maps by combining the additional high-resolution RGB input when upsampled a low-resolution depth map together with a weighting scheme that favors structure details.
Proceedings ArticleDOI

Space-time Neural Irradiance Fields for Free-Viewpoint Video

TL;DR: In this article, a spatiotemporal neural irradiance field for dynamic scenes from a single video is learned by constraining the time-varying geometry of the scene representation using the scene depth estimated from video depth estimation methods.
References
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Proceedings ArticleDOI

KinectFusion: Real-time dense surface mapping and tracking

TL;DR: 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, which fuse all of the depth data streamed from a Kinect sensor into a single global implicit surface model of the observed scene in real- time.
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