Monocular 3D Reconstruction Using Depth Cues from Planar Range Data - PowerPoint PPT Presentation

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Monocular 3D Reconstruction Using Depth Cues from Planar Range Data Ben Eckart Heather Justice Joe Lisee 1 Motivation Eckart, Justice, Lisee 2 Motivation Laser-Level Obstacles Above-Laser Obstacles Eckart, Justice, Lisee 3 Project

Monocular 3D Reconstruction Using Depth Cues from Planar Range Data Ben Eckart Heather Justice Joe Lisee 1
Motivation Eckart, Justice, Lisee 2
Motivation Laser-Level Obstacles Above-Laser Obstacles Eckart, Justice, Lisee 3
Project Goal • Generate best possible depth map from planar LIDAR and single camera 3-D Depth Reconstruction from a Single Still Image , Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng. International Journal of Computer Vision , Aug 2007. Eckart, Justice, Lisee 4
Depth Estimation from Single Images Make3D: Learning 3-D Scene Structure from a Single Still Image , Ashutosh Saxena, Min Sun, Andrew Y. Ng, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008. Eckart, Justice, Lisee 5
Augmenting with Planar LIDAR • Match LIDAR scan to superpixels • Treat LIDAR as ground truth depth • Account for uncertainty in LIDAR data Eckart, Justice, Lisee 6
Questions 7

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Monocular 3D Reconstruction Using Depth Cues from Planar Range Data - PowerPoint PPT Presentation

Monocular 3D Reconstruction Using Depth Cues from Planar Range Data Ben Eckart Heather Justice Joe Lisee 1 Motivation Eckart, Justice, Lisee 2 Motivation Laser-Level Obstacles Above-Laser Obstacles Eckart, Justice, Lisee 3 Project

3D RECONSTRUCTION Reconstruction method Reconstruction from images Reconstruction from video

Probabilistic Tracking and Probabilistic Tracking and Probabilistic Tracking and Reconstruction

Delaunay Triangulation: Applications Reconstruction Meshing 1 Reconstruction From points 2 -

DeepCap: Monocular Human Performance Capture Using Weak Supervision Marc Habermann, Weipeng Xu ,

Monocular Visual-Inertial SLAM for ISMAR SLAM Challenge Jie PAN Shaozu CAO, Jie PAN, Jieqi SHI,

Monocular Vision Based Obstacle Avoidance: A Literature Review Outline Introduction

1. Reconstruction and the West 1.1 Reconstruction: Americas Unfinished Revolution, 1865-1877

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Volumetric Scene Reconstruction Volumetric Scene Reconstruction Goal Goal from Multiple

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Monocular 3D Reconstruction Using Depth Cues from Planar Range Data - PowerPoint PPT Presentation

Monocular 3D Reconstruction Using Depth Cues from Planar Range Data Ben Eckart Heather Justice Joe Lisee 1 Motivation Eckart, Justice, Lisee 2 Motivation Laser-Level Obstacles Above-Laser Obstacles Eckart, Justice, Lisee 3 Project

3D RECONSTRUCTION Reconstruction method Reconstruction from images Reconstruction from video

Probabilistic Tracking and Probabilistic Tracking and Probabilistic Tracking and Reconstruction

Delaunay Triangulation: Applications Reconstruction Meshing 1 Reconstruction From points 2 -

DeepCap: Monocular Human Performance Capture Using Weak Supervision Marc Habermann, Weipeng Xu ,

Monocular Visual-Inertial SLAM for ISMAR SLAM Challenge Jie PAN Shaozu CAO, Jie PAN, Jieqi SHI,

Monocular Vision Based Obstacle Avoidance: A Literature Review Outline Introduction

1. Reconstruction and the West 1.1 Reconstruction: Americas Unfinished Revolution, 1865-1877

Vertex reconstruction Vertex reconstruction in large liquid scintillator detectors in large

Volumetric Scene Reconstruction Volumetric Scene Reconstruction Goal Goal from Multiple

Design of Geofoam Embankment for the I-15 Reconstruction I 15 Reconstruction Steven F. Bartlett,

Curve and surface reconstruction Steve Oudot Reconstruction Paradigm Q What do you see? Why?

Type Reconstruction and Polymorphism 1 Type Checking and Type Reconstruction We now come to the

S Surface f Reconstruction Digitalisierung Surface Reconstruction: Dr. Peer Stelldinger WS

Advanced Methods for Data Processing and Reconstruction Accelerating Reconstruction on advanced

Surface Reconstruction Level Sets Computer Graphics Hoppe et al, Surface reconstruction from

Spectral Surface Reconstruction Nils Erik Flick January 13, 2009 Surface Reconstruction

Persistent self-supervised learning principle: from stereo to monocular vision for obstacle

Obstacle Avoidance for Monocular Drones Table of Contents I. Technological context II. Neural

R eal Time Lethbridge Entrepreneurial iGEM Team iGEM World Jamboree November 3 rd , 2013 Our

Real-Time Monocular SLAM Andrew Davison Robot Vision Group Department of Computing Imperial

Agribot Sprayer, SLAM, and Robust Navigation Andrey Kurenkov, Troy ONeal, Pavel Komarov

Deep Incremental Scene Understanding Federico Tombari &amp; Christian Rupprecht Technical

AR with head-mounted Displays Vorlesung Augmented Reality Prof. Dr. Andreas Butz WS

Single-View Depth Image Estimation Fangchang Ma PhD Candidate at MIT (Sertac Karaman Group)

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Sambuz

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Deep Incremental Scene Understanding Federico Tombari & Christian Rupprecht Technical