IEEE/RSJ IROS 2008 Real-time Tracker

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This slides were for presentation in IROS 2008 conference.

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Real-time 3D Object Pose Estimation and Tracking for Natural Landmark Based Visual Servo Seung-Min Baek and Sukhan Lee Sungkyunkwan University Intelligent System Research Center Changhyun Choi Georgia Tech College of Computing

Contents ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

Introduction ,[object Object],[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

Introduction Many systems still use Artificial Landmark . Unnatural in human environment IEEE/RSJ IROS 2008, Sept 25

Introduction ,[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

Introduction ,[object Object],SIFT about 200~300 ms on a modern PC Structured light several seconds IEEE/RSJ IROS 2008, Sept 25

Motivation ,[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

Related Works ,[object Object],[object Object],[object Object],[object Object],[ L. Vacchetti et al., PAMI 04 ] Input image should be close enough to the prior knowledge! IEEE/RSJ IROS 2008, Sept 25

Related Works ,[object Object],[object Object],[object Object],[G. Panin and A. Knoll, JMM 04 ] Potential danger in background having same color with tracking object! IEEE/RSJ IROS 2008, Sept 25

Our Idea ,[object Object],[object Object],[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

System Overview ,[object Object],IEEE/RSJ IROS 2008, Sept 25

Two Modes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

Problem Definition – Mono Mode ,[object Object],IEEE/RSJ IROS 2008, Sept 25

Problem Definition – Stereo Mode ,[object Object],IEEE/RSJ IROS 2008, Sept 25

Initial Pose Estimation ,[object Object],IEEE/RSJ IROS 2008, Sept 25

Initial Pose Estimation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

Initial Pose Estimation ,[object Object],[object Object],[object Object],[object Object],R,t R,t IEEE/RSJ IROS 2008, Sept 25

Initial Pose Estimation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

Initial Pose Estimation + : SIFT points • : KLT points IEEE/RSJ IROS 2008, Sept 25

Initial Pose Estimation Treat the surface as locally flat IEEE/RSJ IROS 2008, Sept 25

Local Pose Estimation ,[object Object],IEEE/RSJ IROS 2008, Sept 25

Local Pose Estimation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],R,t R,t IEEE/RSJ IROS 2008, Sept 25

Removing Outliers IEEE/RSJ IROS 2008, Sept 25

Outlier Handling ,[object Object],[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

Tracking Results IEEE/RSJ IROS 2008, Sept 25

Experiment Mono Mode Stereo Mode IEEE/RSJ IROS 2008, Sept 25

Tracking Results - translation IEEE/RSJ IROS 2008, Sept 25

Tracking Results - rotation IEEE/RSJ IROS 2008, Sept 25

RMS Error RMS errors over the whole sequence of image Z IEEE/RSJ IROS 2008, Sept 25

Computational Time Computational times of pose estimation IEEE/RSJ IROS 2008, Sept 25

Computational Time Computational times of each module IEEE/RSJ IROS 2008, Sept 25

Summary & Conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

Future Work ,[object Object],[object Object],[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

Thank you ,[object Object],[object Object],[object Object],IEEE/RSJ IROS 2008, Sept 25

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IEEE/RSJ IROS 2008 Real-time Tracker

1. Real-time 3D Object Pose Estimation and Tracking for Natural Landmark Based Visual Servo Seung-Min Baek and Sukhan Lee Sungkyunkwan University Intelligent System Research Center Changhyun Choi Georgia Tech College of Computing

4. Introduction Many systems still use Artificial Landmark . Unnatural in human environment IEEE/RSJ IROS 2008, Sept 25

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15.

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20. Initial Pose Estimation + : SIFT points • : KLT points IEEE/RSJ IROS 2008, Sept 25

21. Initial Pose Estimation Treat the surface as locally flat IEEE/RSJ IROS 2008, Sept 25

22.

23.

24. Removing Outliers IEEE/RSJ IROS 2008, Sept 25

25.

26. Tracking Results IEEE/RSJ IROS 2008, Sept 25

27. Experiment Mono Mode Stereo Mode IEEE/RSJ IROS 2008, Sept 25

28. Tracking Results - translation IEEE/RSJ IROS 2008, Sept 25

29. Tracking Results - rotation IEEE/RSJ IROS 2008, Sept 25

30. RMS Error RMS errors over the whole sequence of image Z IEEE/RSJ IROS 2008, Sept 25

31. Computational Time Computational times of pose estimation IEEE/RSJ IROS 2008, Sept 25

32. Computational Time Computational times of each module IEEE/RSJ IROS 2008, Sept 25

33.

34.

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IEEE/RSJ IROS 2008 Real-time Tracker

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