We present the first dense SLAM system capable of reconstructing non-rigidly deforming scenes in real-time, by fusing together RGBD scans captured from commodity sensors. Our DynamicFusion approach reconstructs scene geometry whilst simultaneously estimating a dense volumetric 6D motion field that warps the estimated geometry into a live frame. Like KinectFusion, our system produces increasingly denoised, detailed, and complete reconstructions as more measurements are fused, and displays the updated model in real time. Because we do not require a template or other prior scene model, the approach is applicable to a wide range of moving objects and scenes.

/pdf/dynamicfusion-reconstruction-and-tracking-of-non-rigid-2c3vjxgb6q.pdf

DynamicFusion: Reconstruction and tracking of non-rigid scenes in real-time

We present a novel approach to real-time dense visual SLAM. Our system is capable of capturing comprehensive dense globally consistent surfel-based maps of room scale environments explored using an RGB-D camera in an incremental online fashion, without pose graph optimisation or any postprocessing steps. This is accomplished by using dense frame-tomodel camera tracking and windowed surfel-based fusion coupled with frequent model refinement through non-rigid surface deformations. Our approach applies local model-to-model surface loop closure optimisations as often as possible to stay close to the mode of the map distribution, while utilising global loop closure to recover from arbitrary drift and maintain global consistency.

http://www.roboticsproceedings.org/rss11/p01.pdf

ElasticFusion: Dense SLAM Without A Pose Graph

Near-infrared (NIR) solid-state micro/nanolasers are important building blocks for true integration of optoelectronic circuitry.1 Although significant progress has been made in III–V nanowire lasers with achieving NIR lasing at room temperature,2−4 challenges remain including low quantum efficiencies and high Auger losses. Importantly, the obstacles toward integrating one-dimensional nanowires on the planar ubiquitous Si platform need to be effectively tackled. Here we demonstrate a new family of planar room-temperature NIR nanolasers based on organic–inorganic perovskite CH3NH3PbI3-aXa (X = I, Br, Cl) nanoplatelets. Their large exciton binding energies, long diffusion lengths, and naturally formed high-quality planar whispering-gallery mode cavities ensure adequate gain and efficient optical feedback for low-threshold optically pumped in-plane lasing. We show that these remarkable wavelength tunable whispering-gallery nanolasers can be easily integrated onto conductive platforms (Si, Au, indium tin oxide...

Room-temperature near-infrared high-Q perovskite whispering-gallery planar nanolasers.

We present a novel approach to real-time dense visual simultaneous localisation and mapping. Our system is capable of capturing comprehensive dense globally consistent surfel-based maps of room scale environments and beyond explored using an RGB-D camera in an incremental online fashion, without pose graph optimization or any post-processing steps. This is accomplished by using dense frame-to-model camera tracking and windowed surfel-based fusion coupled with frequent model refinement through non-rigid surface deformations. Our approach applies local model-to-model surface loop closure optimizations as often as possible to stay close to the mode of the map distribution, while utilizing global loop closure to recover from arbitrary drift and maintain global consistency. In the spirit of improving map quality as well as tracking accuracy and robustness, we furthermore explore a novel approach to real-time discrete light source detection. This technique is capable of detecting numerous light sources in indoo...

ElasticFusion: Real-time dense SLAM and light source estimation

We present an approach to indoor scene reconstruction from RGB-D video. The key idea is to combine geometric registration of scene fragments with robust global optimization based on line processes. Geometric registration is error-prone due to sensor noise, which leads to aliasing of geometric detail and inability to disambiguate different surfaces in the scene. The presented optimization approach disables erroneous geometric alignments even when they significantly outnumber correct ones. Experimental results demonstrate that the presented approach substantially increases the accuracy of reconstructed scene models.

/pdf/robust-reconstruction-of-indoor-scenes-1drcfrfeu2.pdf

Robust reconstruction of indoor scenes

We present a comprehensive overview of the stereoscopic Intel RealSense RGBD imaging systems. We discuss these systems' mode-of-operation, functional behavior and include models of their expected performance, shortcomings, and limitations. We provide information about the systems' optical characteristics, their correlation algorithms, and how these properties can affect different applications, including 3D reconstruction and gesture recognition. Our discussion covers the Intel RealSense R200 and RS400.

Intel(R) RealSense(TM) Stereoscopic Depth Cameras

We present a comprehensive overview of the stereoscopic Intel RealSense RGBD imaging systems We discuss these systems' mode-of-operation, functional behavior and include models of their expected performance, shortcomings, and limitations We provide information about the systems' optical characteristics, their correlation algorithms, and how these properties can affect different applications, including 3D reconstruction and gesture recognition Our discussion covers the Intel RealSense R200 and the Intel RealSense D400 (formally RS400)

Intel RealSense Stereoscopic Depth Cameras

We present a comprehensive overview of the stereoscopic Intel RealSense RGBD imaging systems. We discuss these systems' mode-of-operation, functional behavior and include models of their expected performance, shortcomings, and limitations. We provide information about the systems' optical characteristics, their correlation algorithms, and how these properties can affect different applications, including 3D reconstruction and gesture recognition. Our discussion covers the Intel RealSense R200 and the Intel RealSense D400 (formally RS400).

/pdf/intel-realsense-stereoscopic-depth-cameras-1zjni51adf.pdf

Recent advances have allowed for the creation of dense, accurate 3D maps of indoor environments using RGB-D cameras. Some techniques are able to create large-scale maps, while others focus on accurate details using GPU-accelerated volumetric representations. In this work we describe patch volumes, a novel multiple-volume representation which enables the creation of globally consistent maps of indoor environments beyond the capabilities of previous high-accuracy volumetric representations.

Patch Volumes: Segmentation-Based Consistent Mapping with RGB-D Cameras

Single crystal films of 4′-dimethylamino-N-methyl-4-stilbazolium tosylate (DAST) with excellent optical quality have been prepared by modified shear method. Electro-optic modulation for light propagating perpendicular to the film surface was measured at a wavelength (720 nm) where absorption is small. Very large electro-optic modulation (20%) was demonstrated in a 3 μm thick film at a low ac field (1 V/μm, at 4 kHz). Electro-optic modulation in such thin films is suitable for a wide range of applications in free-space interconnects and various modulator structures with light propagating perpendicular to the film. The magnitude of the electro-optic coefficient at 720 nm, r11∼530 pm/V, is significantly larger than that of bulk crystals.

Achintya K. Bhowmik

Papers

Intel(R) RealSense(TM) Stereoscopic Depth Cameras

Intel RealSense Stereoscopic Depth Cameras

Intel RealSense Stereoscopic Depth Cameras

Patch Volumes: Segmentation-Based Consistent Mapping with RGB-D Cameras

Single-pass thin-film electro-optic modulator based on an organic molecular salt