efficient 2d-to-3d correspondence filtering for scalable 3d object recognition 2014-10-07...

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object

Recognition

2014-10-07Yeong-Jun Cho

Computer Vision and Pattern Recognition,2013

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Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition– Introduction– Methods– Results– Conclusion

Conclusion

Contents

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Efficient 2D-to-3D Correspondence Fil-tering

for Scalable 3D Object Recognition

CVPR 2013

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Introduction

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

• 2D-to-3D matching 을 통한 3D Object recognition

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Introduction

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

• Query Image 와 3D object models 과의 모든 correspondences 를 구함• 2D feature 로는 DAISY 사용 /

Searching 기법으로는 ANN(approximate nearest neighbor) 사용

InlierOutlierCorrespondences

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Introduction

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

• 모델별로 RANSAC 을 통해 최종 inlier 를 선별최초 matching 결과의 outlier 가 많으면 많은 RANSAC iteration 을 요구함 . ( 수행 시간 증가 )

뿐만 아니라 , RANSAC 정확도가 떨어져 recognition recall 이 떨어질 수 있음 . ( 인식 정확도 하락 )

InlierOutlierCorrespondences

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Introduction

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

• 따라서 , 최초 matching 시의 Outlier 를 빠르고 효과적으로 제거하는 기법을 제안 (Correspondence filtering)

▶ 수행속도 개선 , 인식 정확도 개선

InlierOutlier

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Introduction– 문제 정의 (outlier 종류 기술 )

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

• 배경과 matching

• 다른 model 과 matching

• 같은 model 과 matching 되었으나 ,올바르지 않은 위치에 matching

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Introduction– 문제 정의 (outlier 종류 기술 )

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

• 배경과 matching

• 다른 model 과 matching

• 같은 model 과 matching 되었으나 ,올바르지 않은 위치에 matching

Statistics & geometric cues 를 통한 outlier 제거

Global filtering

Local filtering

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Methods– Local filtering for removing

• Authors observed that are irregularly distrib-uted

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

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Methods– Local filtering for removing

• Authors observed that are irregularly distrib-uted

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

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Methods– Local filtering for removing

• Authors observed that are irregularly distrib-uted

• 2D local consistency check

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

scene

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Methods– Local filtering for removing

• Authors observed that are irregularly distrib-uted

• 2D local consistency check

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

scene

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Methods– Local filtering for removing

• Authors observed that are irregularly distrib-uted

• 2D-3D local consistency check

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

2D-3D local consistency check

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Methods– Global filtering for removing

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

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Methods

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

𝒒𝒊 𝒒 𝒋

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Methods

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

𝒒𝒊

𝒒 𝒋𝒑 𝒋

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Methods

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

𝒒𝒊

𝒒 𝒋𝒑 𝒋

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Methods

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

상대적으로 강한 연결이 되지 않은 vertex 는 로 판단하여 제거

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Experimental results

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

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Experimental results

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

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Conclusion

– 각 correspondence 분포를 고려한 Local filtering 과– Pairwise 한 위치 관계를 고려한 Global filtering 을 통한

outlier correspondences 제거

> 수행 속도 향상 및 인식 정확도 향상

Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition

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Q & A