Robotics and Computer Vision Lab


Extra Form
저 자 Jun-sik Kim
논문일시(Year) 2006
논문일시(Month) 02
김준식, 랭크 부족관계를 이용한 비보정 영상으로부터의 메트릭 복원, 한국과학기술원, 2006, 2월.

Inferring geometric information from images has been dealt with very importantly in computer vision area.
In this work, we aim to reconstruct a metric structure of a scene from images using the fact that the conic dual to the circular points has a simple diagonal rank-deficient form. By manipulating image's features to constrain the simple diagonal form algebraically, the metric invariants of an observed scene can be recovered.

In the first part of the work, we use "concentric circles" as basic features, and we propose simple "subtraction methods" to find affine and metric properties of a plane with concentric circles. The geometric meanings of the resulting subtraction matrices are revealed. Some experiments are conducted to show the possibilities to use the proposed algorithm, including a calibration of a multi-camera system. As a direct extension, the concentric circle cases are generalized to deal with some general conics whose foci are known and confocal conics whose foci are unknown.

In the second part of the work, we propose an "addition method" using one-dimensional basic features such as points and lines. To analyze the geometric information efficiently, we build a new space called "semi-metric space." The parameterization of metric invariants in the semi-metric space is made, and using that, the physical meanings of the parameters of the invariants are derived. Although we cannot measure the scene metrically, some knowledge about the structure of the scene can be retrieved from images, by using only easily obtainable features such as parallelism and orthogonality. Under static camera assumption and with more images, the metric of the planes can be determined.

In the third part of the work, we propose a framework to unify the geometric constraints used in camera calibration and in metric reconstruction. The previously used constraints are revisited and reinterpreted in the proposed framework. We show that all kinds of scene constraints can be converted into the forms of constraints on the cameras, and the methods in the first and the second parts of the work are useful to make the unified framework. We show that the unified framework have benefits to analyze the various types of constraints. A more flexible algorithm to metric-reconstruct scenes from images is developed to show the feasibility of our proposed unified framework.

List of Articles
23. Robust Low-rank Optimization with Priors
Tae-Hyun Oh
KAIST 2017 / 5
22. A Novel Low-Rank Constraint Method with the Sparsity Model for Moving Object Analysis
Tae-Hyun Oh
KAIST 2012 / 08
21. [Book] Metric Invariants for Camera Calibration: Designing algorithms from algebraic rank analysis
Jun-sik Kim, In So Kweon
LAP LAMBERT Academic Publishing (October 4, 2011) 2011 / 10
20. [BOOK] Catadioptric Vision for Robotic Applications
Jean-Charles Bazin, In So Kweon
LAMBERT Academic Publishing 2011 / 01
19. [Book] Object Identification and Categorization with Visual Context
Sungho Kim, In So Kweon
KAIST 2008 / 05
18. Hierarchical Graphical Model-based Methods for Object Identification and Categorization with Visual Context
Sungho Kim
KAIST 2007 / 02
» Metric reconstruction from images using rank-deficient relations
Jun-sik Kim
KAIST 2006 / 02
16. Robust Correspondence Search under Photometric Variations and Image Ambiguity
Kukjin Yoon
KAIST 2006 / 02
15. Catadioptric vision based localization and mapping for indoor mobile robot
Gijeong Jang
KAIST 2005 / 08
14. Appearance-cloning : Photo-consistent 3D modeling from multi-view images
Howon Kim
KAIST 2004 / 08
13. Shot Detection and Temporal Interest Point for Event-based Clustering and its Application to Golf Videos
Seunghoon Han
KAIST 2004 / 08
12. High-speed automatic edge detection using pixel group statistics and fuzzy-based automatic thresholding
Dongsu Kim
KAIST 2003 / 02
11. Image-based Visual Servoing for Linear Path Control
Jaeseung Cho
KAIST 2002 / 08
10. Chromatic invariant based image retrieval for three dimensional objects
Jiyeun Kim
KAIST 2002 / 02
9. Mobile robot navigation using fuzzy based sensor fusion
Wangheon Lee
KAIST 2001 / 08
8. Robust and direct estimation of camera motion and 3-D structure from stereo image sequence
Seongkee Park
KAIST 2000 / 08
7. A biprism stereo camera system
Doohyun Lee
KAIST 2000 / 08
6. Robust motion estimation and statistical change detection in image sequences under time-varying illumination
Youngsu Moon
KAIST 2000 / 08
5. 3D structure recovery and motion segmentation using uncalibrated cameras
Jongeun Ha
KAIST 2000 / 02
4. Optimization-based approaches in computer vision
Dongjoong Kang
KAIST 1999 / 02
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