Full Body Scanning by Daniel Evora

Calibration

Left & Right

Mesh

101158 triangles

3D RECONSTRUCTION USING STRUCTURED LIGHT by Stefanie Handojo

COMPSCI 117

PROJECT IN COMPUTER VISION

STEFANIE HANDOJO

Extracting 2D Points from the images

Decode Construct the 3D Points

Triangulation

Create Mesh Getting Rid of Long edges / Far away Neighbors

Filling Holes and Mesh Smoothing

Mesh Alignment Combining Meshes into Final Model Poisson Surface Reconstruction Software

Josh Tutwiler

• Goal: to construct a 3-D model of a bowling pin from 2-D images.

Smooth the Mesh

• nbr_smooth– Move each point to the mean of its neighbors

Meshes

Computer Vision Default Project by Patrick Flynn

Original Image

Computer Vision Default Project

Image Scans – 3 viewpoints

Computer Vision Default Project

Manually Cleaned Up

Computer Vision Default Project

Aligned with my ICP (lsqnonlin)

Default Project by Phong VuongRight

Left

Mesh Cleaning

Mesh Alignment

Poisson Surface Reconstruction

Default Project by Roula Lagaditis

Chosen Object: Bender-bot

Using structured light, recovered front, back, right and left

Default Project

Chosen Object: Bender-bot

Mesh Aligning - Front and Back scanned images, using “rigid-alignment”

Default Project

Chosen Object: Bender-botFinal recovered shape

CS117 Final ProjectDanny Miller

3 objects

~ 7 scans per object

~ 2 GB of pictures

Idea – adding a green backdrop could make it easy to filter out the background

Green tablecloth from Party City - 79¢

Green Removal

• Created a windows program in C# to remove the green from pictures.

Problems - Reflectivity

Scans

• 5 stage scanning process– Auto-Pruning

• Several passes

– User Pruning• 3 views in 2d• 30 views in 2d

– Smoothing• Several passes

– Normals– Colors

Alignment

• Using the linear algebra approach

Color?

Mesh Creation

Object Centric Photo BrowsingTony Tran

Input

Part3: Estimating relationship between images.Image i’s sift points Image j’s.sift points

Input:

Find Correspondences(matches)

Compute Essential matrixand remove outlier matches RANSAC

E

Remove incoherent matchesbased on a triangulation heuristic

Remove bad matchesWith triangulation heuristic

CS 117 Project: Motion CaptureBy Blake Atkinson

• Materials• 5 different colored sets of

appx. 3v LEDs

• Electrical tape

• Glove

• 9v Batteries

• Red and Black Wire

• More patience than you have

Since the epipolar lines are calculated using the Fundamental Matrix, which is calculated from your initial SIFT points, they too should land on the epipolar lines. If not you’ve done something wrong. Here we have the SIFT points (red & yellow) and the corresponding epipolar lines (blue) based on those points. The left image gets it’s epipolar equations from the right points, and vice versa.

Epipolar Geometry by Nick Schiffelbein

Automating Camera CalibrationSam Hallman

But how do you solve for a matrix??

Try #2 with the MK symbol