Image Based 3D Modeling 以二維影像資料重建三維物體模型

Image Based 3D Modeling以二維影像資料重建三維物體模型指導教授:劉興民教授專題生:張鈞皓、蕭宥騰、裴家佑

Outline • Introduction • Data flow & Environments • Method • Bundler • PMVS • Mesh • Result

What is this Image Based 3D Modeling? An automatic process which transforms photos into a virtual 3D model. AutomaticModeling Process Photos 3Dmodel

Motivation: • Those modeling methods are old fashioned. For example: 1. Artificial modeling spends too much time. 2. Special modeling hardware costs too much. • A fast modeling method significantly improves development of virtual reality.

Implementation Outline

Environments • 開發系統： Cygwinon Windows (C/C++) • 相關工具： • Meshlab • Imagemagick

Implementation method Input: 對目標環場拍攝之照片(15~20張、照片中之物體必須有重疊性存在) 步驟: 1.讀取照片EXIF資訊並分析拍攝相對位置 2.從二維相片找出三維資訊 3.輸出圖片關係 4.corner detection進階特徵分析 5.三角化重建產生密點雲

Implementation method • Bundler： • 實作Structure form motion • PMVS： • 利用照片資訊，產生點雲

Structure from motion • 從二維影像得到三維的資訊（影像間須有重疊性） • 觀察者和物體必須有相對運動

特徵點分析 • Use SIFT

判斷點相關性 • 建立K-dimension tree • 找出涵蓋範圍最大的cut dimension，以此cut dimension的數值為依據建立子樹 • 方法一：以平均值將點分給兩邊子樹 • 方法二：將點平均分配給兩邊子樹，即找尋點的中位數

Improvement We have modified the feature detection method of API to improve the quality of result. Before After

特徵點對應 • approximate nearest neighbors • RANdomSAmple Consensus

corner detection • Harris corner detector • Difference of Gaussian

Expand the feature points • Use Triangular Reconstruct • 相鄰的點具有相似的法向量與位置 • 過濾處理，剔除灰度一致性、幾何一致性較弱的面

Mesh • Use meshlab • method： • Ball pivoting

Result The final result is a point cloud. Point cloud is consisted of lots of points. Each points is represented by 3D coordinate and color. Photos 3D model

Comparison between different resolutions The resolution has positive relation to the quality of result and processing time. 80% 60% 40% 20

END • Thank you for listening

Image Based 3D Modeling 以二維影像資料重建三維物體模型