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Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 2014-10-07 Yeong-Jun Cho Computer Vision and Pattern Recognition,2013.

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Presentation on theme: "Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 2014-10-07 Yeong-Jun Cho Computer Vision and Pattern Recognition,2013."— Presentation transcript:

1 Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 2014-10-07 Yeong-Jun Cho Computer Vision and Pattern Recognition,2013

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

3 Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition CVPR 2013 3

4  Introduction Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 4 2D-to-3D matching 을 통한 3D Object recognition

5  Introduction Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 5 Query Image 와 3D object models 과의 모든 correspondences 를 구함 2D feature 로는 DAISY 사용 / Searching 기법으로는 ANN(approximate nearest neighbor) 사용 Inlier Outlier Correspondences

6  Introduction Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 6 모델별로 RANSAC 을 통해 최종 inlier 를 선별 최초 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 ) Inlier Outlier Correspondences

7  Introduction Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 7 따라서, 최초 matching 시의 Outlier 를 빠르고 효과적으로 제거하는 기법을 제안 (Correspondence filtering) ▶ 수행속도 개선, 인식 정확도 개선 Inlier Outlier

8  Introduction – 문제 정의 (outlier 종류 기술 ) Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 8 배경과 matching 다른 model 과 matching 같은 model 과 matching 되었으나, 올바르지 않은 위치에 matching

9  Introduction – 문제 정의 (outlier 종류 기술 ) Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 9 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

10  Methods –Local filtering for removing Authors observed thatare irregularly distributed Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 10

11  Methods –Local filtering for removing Authors observed thatare irregularly distributed Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 11

12  Methods –Local filtering for removing Authors observed thatare irregularly distributed 2D local consistency check Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 12 scene

13  Methods –Local filtering for removing Authors observed thatare irregularly distributed 2D local consistency check Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 13 scene

14  Methods –Local filtering for removing Authors observed thatare irregularly distributed 2D-3D local consistency check Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 14 2D-3D local consistency check

15  Methods –Global filtering for removing Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 15

16  Methods Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 16

17  Methods Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 17

18  Methods Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 18

19  Methods Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 19 상대적으로 강한 연결이 되지 않은 vertex 는 로 판단하여 제거

20  Experimental results Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 20

21  Experimental results Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition 21

22  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 22

23 Q & A 23


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