Reconstruction of 3D image for Indoor scene

S1150046 Naoki Okazaki

Outline・Forecast・Motivation and Problem Statement・Related Work・Method・Result - case 1 : SIFT - case 2 : 2DCDP・Summary and Future Work・Backup Slides

ForecastSIFT 2DCDP

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Motivation and Problem Statement

and

Wall Floor Difficult for Reconstruction

The present conditions:

The improvement of the problem :

3D reconstruction in indoor environment closer

Related WorkThe result of past study of 3D reconstruction in indoor environment :

This system uses existing some packages and algorithms

Study of the comparison of SIFT and 2DCDP performed in the past :

This study shows utility of 2DCDP from a result of provided Matching points and Number of polygons.

MethodApply a common image data set to two packages :

1. Bundler Structure from Motion package (SIFT case)

2. 2DCDP by my Lab

- Developed by Noah Snavely- SIFT algorithm can describe characteristics of feature points that are invariant to scale and rotation changes.

- Developed by Yaguchi, Iseki, and Oka- 2DCDP preserves 2D pixel correlation and assures continuity and monotonicity in the input image.

Search

・ Matching points・ Calculation time

One of data image

Result - Case of SIFTThe data obtained

・ Matching points : 75,000 points・ Calculation time : 24 hours Details still under investigation

The reconstructed 3D image by obtained data

Bookshelf

Three lines of desks

PC rack

Panel

Result - Case of 2DCDP

・ Matching points : ・ Calculation time :

The data obtained

//I'm sorry. My experiment is not yet over.

Summary and Future Work

//I'm sorry. My experiment is not yet over.

Back up

//I'm sorry. My experiment is not yet over.