A Theft-Based Approach to 3D Object Acquisition Ronit Slyper Jim McCann.

Slides:



Advertisements
Similar presentations
KinectFusion: Real-Time Dense Surface Mapping and Tracking
Advertisements

Computer Vision Spring ,-685 Instructor: S. Narasimhan Wean 5403 T-R 3:00pm – 4:20pm Lecture #17.
Vision Sensing. Multi-View Stereo for Community Photo Collections Michael Goesele, et al, ICCV 2007 Venus de Milo.
Gratuitous Picture US Naval Artillery Rangefinder from World War I (1918)!!
Computational Geometry Definition and Application Areas.
W HAT IS IT ? Point cloud - Set of vertices in a 3D coordinate system. These vertices are usually defined by X, Y, and Z coordinates, and typically are.
Structured Light + Range Imaging Lecture #17 (Thanks to Content from Levoy, Rusinkiewicz, Bouguet, Perona, Hendrik Lensch)
Adviser:Ming-Yuan Shieh Student:shun-te chuang SN:M
The Disputed Federalist Papers : SVM Feature Selection via Concave Minimization Glenn Fung and Olvi L. Mangasarian CSNA 2002 June 13-16, 2002 Madison,
Implementation of ICP Variants Pavan Ram Piratla Janani Venkateswaran.
Computing 3D Geometry Directly From Range Images Sarah F. Frisken and Ronald N. Perry Mitsubishi Electric Research Laboratories.
Advanced Computer Graphics (Spring 2006) COMS 4162, Lecture 8: Intro to 3D objects, meshes Ravi Ramamoorthi
An Efficient Representation for Irradiance Environment Maps Ravi Ramamoorthi Pat Hanrahan Stanford University.
Speed and Robustness in 3D Model Registration Szymon Rusinkiewicz Princeton University.
SIGGRAPH Course 30: Performance-Driven Facial Animation Section: Markerless Face Capture and Automatic Model Construction Part 2: Li Zhang, Columbia University.
Advanced Computer Graphics (Fall 2010) CS 283, Lecture 4: 3D Objects and Meshes Ravi Ramamoorthi
3D Scanning. How can we get the form? Projection.
Efficient Variants of the ICP Algorithm
Representations of Visual Appearance COMS 6160 [Spring 2007], Lecture 4 Image-Based Modeling and Rendering
A Laser Range Scanner Designed for Minimum Calibration Complexity James Davis, Xing Chen Stanford Computer Graphics Laboratory 3D Digital Imaging and Modeling.
Real-Time 3D Model Acquisition
Famous Images in Computer Graphics & Image Processing Sérgio Leal N.o Erasmus student at: Institute for Computer Graphics and Vision Technical.
Computer Science Department
Spectral Processing of Point-sampled Geometry
3D full object reconstruction from kinect Yoni Choukroun Elie Semmel Advisor: Yonathan Afflalo.
 Marc Levoy IBM / IBR “The study of image-based modeling and rendering is the study of sampled representations of geometry.”
 Marc Levoy IBM / IBR “The study of image-based modeling and rendering is the study of sampled representations of geometry.”
Volume Rendering & Shear-Warp Factorization Joe Zadeh January 22, 2002 CS395 - Advanced Graphics.
2D TO 3D MODELLING KCCOE PROJECT PRESENTATION Student: Ashish Nikam Ashish Singh Samir Gaykar Sanoj Singh Guidence: Prof. Ashwini Jaywant Submitted by.
Structured light and active ranging techniques Class 8
9/13/2015Memorial University of Newfoundland Faculty of Engineering & Applied Science Engineering 7854 Industrial Machine Vision INTRODUCTION TO MACHINE.
Enhanced Navigational Aid For the Visually Impaired Peter Okma (CPE) Abhay Sampath (EE) Katelyn Sapio (EE) 04/28/2010.
KinectFusion : Real-Time Dense Surface Mapping and Tracking IEEE International Symposium on Mixed and Augmented Reality 2011 Science and Technology Proceedings.
Dynamically Reparameterized Light Fields Aaron Isaksen, Leonard McMillan (MIT), Steven Gortler (Harvard) Siggraph 2000 Presented by Orion Sky Lawlor cs497yzy.
Sole Supports Imaging Software Group 9: Edward Krei (BME) Edward Krei (BME) Michael Galante (CompE) Michael Galante (CompE) Derrick Snyder (CompE) Derrick.
MESA LAB Multi-view image stitching Guimei Zhang MESA LAB MESA (Mechatronics, Embedded Systems and Automation) LAB School of Engineering, University of.
Hierarchical Clustering
SURFACE RECONSTRUCTION FROM POINT CLOUD Bo Gao Master’s Thesis December, 2007 Thesis Committee: Professor Harriet Fell Professor Robert Futrelle College.
Reporter: Zhonggui Chen
H. MAINAUD DURAND PACMAN WP1 OUTLINE Tasks & role of associated partner Plans for training.
A Method for Registration of 3D Surfaces ICP Algorithm
Realtime 3D model construction with Microsoft Kinect and an NVIDIA Kepler laptop GPU Paul Caheny MSc in HPC 2011/2012 Project Preparation Presentation.
Major objective of this course is: Design and analysis of modern algorithms Different variants Accuracy Efficiency Comparing efficiencies Motivation thinking.
NSF Engineering Research Center for Reconfigurable Manufacturing Systems College of engineering, University of Michigan 1 Automated Registration for 3D.
A Novel Local Patch Framework for Fixing Supervised Learning Models Yilei Wang 1, Bingzheng Wei 2, Jun Yan 2, Yang Hu 2, Zhi-Hong Deng 1, Zheng Chen 2.
Real-time Rendering of Heterogeneous Translucent Objects with Arbitrary Shapes Stefan Kinauer KAIST (Korea Advanced Institute of Science and Technology)
Course Topics CMSC 635. Ray Tracing Friedrich A Lohmüller, POV-Ray Hall of Fame Gallery.
03/15/03© 2005 University of Wisconsin Where We’ve Been Photo-realistic rendering –Accurate modeling and rendering of light transport and surface reflectance.
04/23/03© 2003 University of Wisconsin Where We’ve Been Photo-realistic rendering –Accurate modeling and rendering of light transport and surface reflectance.
High-Speed Policy-Based Packet Forwarding Using Efficient Multi-dimensional Range Matching Lakshman and Stiliadis ACM SIGCOMM 98.
Greg Humphreys CS445: Intro Graphics University of Virginia, Fall D Object Representations Greg Humphreys University of Virginia CS 445, Fall 2003.
Yizhou Yu Texture-Mapping Real Scenes from Photographs Yizhou Yu Computer Science Division University of California at Berkeley Yizhou Yu Computer Science.
Kijung Shin Jinhong Jung Lee Sael U Kang
Non-Photorealistic Rendering FORMS. Model dependent Threshold dependent View dependent Outline form of the object Interior form of the object Boundary.
Distance Estimation Ohad Eliyahoo And Ori Zakin. Introduction Current range estimation techniques require use of an active device such as a laser or radar.
Multi-objective evolutionary generation of mamdani fuzzy rule-based systems based on rule and condition selection International Workshop On Genetic And.
Real-Time Relief Mapping on Arbitrary Polygonal Surfaces Fabio Policarpo Manuel M. Oliveira Joao L. D. Comba.
CSc Computer Graphics Algorithm Lecture 20 Overview of 3D Modeling Techniques Ying Zhu Georgia State University.
A New Rutting Measurement Method Using Emerging 3D Line-Laser-Imaging System 授課老師:林志棟 老師 研 究 生:薛智聖.
Faculty of Sciences and Technology from University of Coimbra Generating 3D Meshes from Range Data [1] Graphic Computation and Three-dimensional Modeling.
Real-Time 3D Model Acquisition Szymon Rusinkiewicz Olaf Hall-Holt Marc Levoy Ilya Korsunsky Princeton University Stanford University Hunter College.
Trimble LaserAce 1000 Accuracy Evaluation for Indoor Data Acquisition
Advanced Algorithms Analysis and Design
Line Extraction Using 2D Laser Range Finder
Power Control for Data Center
CSc 8820 Advanced Graphics Algorithms
Image Based Modeling and Rendering (PI: Malik)
Objective of This Course
Charles University Prague
Creating a Terrain Surface From LAS Files in ArcView
Presentation transcript:

A Theft-Based Approach to 3D Object Acquisition Ronit Slyper Jim McCann

Outline Previous Work Our Method Results Future Work

Previous Work Commercial  Contact Scanners  Non-contact Scanners Coordinate Measuring Machine Laser Range Finder

Previous Work (continued) Real-Time 3D Model Acquisition (Rusinkiewicz, Hall-Holt, Levoy)  Structured-light rangefinder, iterative closed-points for alignment, point-based merging and rendering algorithms  60 Hz

Weaknesses of Previous Work Inexact  Range / accuracy tradeoff for laser rangefinders  Finite accuracy Computer-intensive  Point alignment, triangulation Stationary objects

Our Method We propose a theft-based object acquisition system  Exact surface and material acquired  No expensive hardware  Data-set may be viewed in real-time with no expensive precomputation  For many objects, acquisition is of low time & space complexity (i.e., trivial)

Methods The exact theft-based method we used is based on a heuristic we call “casing”.  Grab-and-Run  Yoink  Advanced techniques Bribery, subterfuge, etc (see paper)  Under development: The Siggraph Blackmail

Results Stanford bunny model acquisition

Future Work Additional theft-based methods  Ninjas, pirates, grad students Punishment and arrest alleviation  Cache-based approach

Any Questions?