Robotics and Computer Vision Lab

Publications

Extra Form
저 자 Jun-sik Kim
학 회 KAIST
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
225. Robust region boundary tracking in noisy image sequences
Dongjoong Kang, In So Kweon
2nd Japan-Korea Joint Workshop on Computer Vision 1996 / 02
224. Active vision for intelligent vehicles
Dongjoong Kang, In So Kweon
International Workshop on Computer Vision Technology 1996 / 12
223. A visual tracking algorithm by integrating rigid model and snake
Dongjoong Kang, In So Kweon
IEEE International Conference on Intelligent Systems and Robots 1996 / 11
222. A Kalman filter based visual tracking algorithm for an object moving in 3-D
J. Lee, M. Kim, In So Kweon
IEEE International Conference on Intelligent Systems and Robots 1995 / 08
221. A self-localization algorithm for a mobile robot using perspective invariant
Kyoungsig Roh, S. Kim, Wangheon Lee, In So Kweon
International Workshop on Advanced Mechatronics 1995 / 12
220. Active vision algorithms using projective invariants
Dongsu Kim, Kyoungsig Roh, In So Kweon
Annual Conference of Robotics Society in Japan 1994 / 11
219. A new 2-D object recognition algorithm using geometric invariance
Kyoungsig Roh, In So Kweon
International Symposium on Advances in Computer Integrated Manufacturing Systems 1994 / 11
218. Model based color halftoning techniques on perceptually uniform color spaces
C. Kim, S. Kim, Y. Seo, In So Kweon
IST&T/SPIE International Conference on Digital Video Compression and Processing on Personal Computers: Algorithms and Technologies 1994 / 01
217. A behavior-based intelligent robot in dynamic indoor environments
In So Kweon, M. Watanabe, K. Onoguchi, Y. Kuno
IEEE International Conference on Robotics and Automation (ICRA) 1992 / 05
216. behavior-based mobile robot using active sensor fusion
In So Kweon, M. Watanabe, K. Onoguchi, Y. Kuno
IEEE International Conference on Intelligent Robots and Systems (IROS) 1992 / 07
215. A three-layered system architecture for behavior-based mobile robots
M. Watanabe, K. Onoguchi, In So Kweon, Y. Kuno
IEEE International Conference on Robotics and Automation (ICRA) 1992 / 05
214. Vision-based behaviors for indoor mobile robots
In So Kweon, K. Onoguchi, M. Watanabe, Y. Kuno
Information Processing Society of Japan Workshop on Computer Vision 1992 / 01
213. Vehicle control using target tracking
K. Onoguchi, M. Watanabe, In So Kweon, Y. Kuno
Information Processing Society of Japan Workshop on Computer Vision 1991 / 07
212. Extracting topographic terrain features for outdoor mobile robots
In So Kweon, T. Kanade
IEEE International Conference on Robotics and Automation (ICRA) 1991 / 04
211. Behavior-based mobile robot using multiple sensors
In So Kweon, M. Watanabe, K. Onoguchi, Y. Kuno
The 1st Korea-Japan Joint Conference on Computer Vision 1991 / 10
210. High resolution terrain map from multiple sensor data
In So Kweon, T. Kanade
IEEE International Workshop on Intelligent Robots and Systems (IROS) 1990 / 07
209. A mobile robot for lunar surface operations
Bares, In So Kweon, D. Wettegreen, W. Whittaker
NASA Conference on Space Telerobotics 1990 / 03
208. Methods for identifying footfall positions for a legged robot
Caillas, In So Kweon, E. Krotkov, M. Hebert
IEEE International Workshop on Intelligent Robots and Systems (IROS) 1989 / 09
207. Terrain mapping for a roving planetary explorer
M. Hebert, E. Krotkov, In So Kweon, T. Kanade
IEEE International Conference on Robotics and Automation (ICRA) 1989 / 05
206. First results in terrain mapping for a roving planetary explorer
E. Krotkov, M. Hebert, In So Kweon, T.Kanade
NASA Conference on Space Telerobotics 1989 / 01
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