• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.472-474
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• 2002

본 논문에서는 복잡한 영상에서 얼굴 영역의 윤곽선을 검출하는 방법을 제안하였다. 이를 위하여 얼굴의 칼라 정보에 기반한 액티브 컨투어 모델을 이용하였다. 얼굴의 칼라 정보는 색채칼라 공간(chromatic color space)에서 2D-Gaussian모델로 나타내어지는 스킨 칼로 모델로 표현 되었다. 실험결과 제안된 방법은 복잡한 영상뿐 아니라 잡음이 많은 영상에서 하나 또는 여러 개의 얼굴 영역을 추출할 수 있었다.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.527-534
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• 2003

An active contour model called snake is powerful tool for object contour extraction. But, conventional snakes require exhaustive computing time, sometimes can´t extract complex shape contours due to the properties of energy function, and are also heavily dependent on the position and the shape of an initial snake. To solving these problems, we propose in this paper an improved snake called "shaking snake", based on a greedy algorithm. A shaking snake consist of two steps. According to their appropriateness, we in the first step move each points directly to locations where contours are likely to be located. In the second step, we then align some snake points with a tolerable bound in order to prevent local minima. These processes shake the proposed snake. In the experimental results, we show the process of shaking the proposed shake and comparable performance with a greedy snake. The proposed snake can extract complex shape contours very accurately and run fast, approximately by the factor of five times, than a greedy snake.

• Proceedings of the KSRS Conference
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• v.2
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• pp.610-614
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• 2006

In this paper the advanced method of geodesic active contours was developed for the task of building detection from aerial and satellite images. Automatic extraction of man-made structures including buildings, building blocks or roads from remote sensing data is useful for land use mapping, scene understanding, robotic navigation, image retrieval, surveillance, emergency management procedures, cadastral etc. A level set method based on a region-driven segmentation model was implemented with which building boundaries were detected, through this curve propagation technique. The essence of this approach is to optimize the position and the geometric form of the curve by measuring information along that curve, and within the regions that compose the image partition. To this end, one can consider uniform intensities inside objects and the background. Thus, given an initial position of the curve, one can determine global, region-driven functions and provide a statistical description of the inside and outside object area. The calculus of variations and a gradient descent method was used to optimize the variational functional by an iterative steady state process. Experimental results demonstrate the potential of the proposed processing scheme.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.89-92
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• 2001

In this paper, we propose a new approach for tracking a moving object in moving image sequences using active contour models and optical flow. In our approach object segmentation is achieved by active contours, and object tracking is done by motion estimation based on optical flow. To get more dynamic characteristics, Lagrangian dynamics combined to the active contour models. For the optical flow computation, a method, which is based on Spatiotempo-ral Energy Models, is employed to perform robust tracking under poor environments. A prototype real tracking system has been developed and applied to a contents-based video retrieval systems.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1515-1518
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• 2002

This paper proposes an active contour model to detect facial regions in a given image. Accordingly we use the color information human faces which is represented by a skin color model. We evolve the active contour using the level set method which allows for cusps, corners, and automatic topological changes. Experimental results show the effectiveness of the proposed method.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.925-926
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• 2008

This paper presents an object tracking method using motion vectors generated in the MPEG4 encoding process and the snake algorithm for active contours. This paper shows the possibility of realtime object tracking during MPEG4 encoding process in a conventional surveillance system. The experiments is performed on a PC platform to prove the effectiveness of the method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.125-132
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• 2008

Omnidirectional camera system with a wide view angle is widely used in surveillance and robotics areas. In general, most of previous studies on estimating a projection model and the extrinsic parameters from the omnidirectional images assume corresponding points previously established among views. This paper presents a novel omnidirectional camera calibration based on automatic contour matching. In the first place, we estimate the initial parameters including translation and rotations by using the epipolar constraint from the matched feature points. After choosing the interested points adjacent to more than two contours, we establish a precise correspondence among the connected contours by using the initial parameters and the active matching windows. The extrinsic parameters of the omnidirectional camera are estimated minimizing the angular errors of the epipolar plane of endpoints and the inverse projected 3D vectors. Experimental results on synthetic and real images demonstrate that the proposed algorithm obtains more precise camera parameters than the previous method.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.236-246
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• 2006

Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks such as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. In this paper, the development of new snake model called 'adaptive color snake model (ACSM)' for segmentation and tracking is introduced. The simple operation makes the algorithm runs in real-time. For robust tracking, the condensation algorithm was adopted to control the parameters of ACSM. The effectiveness of the ACSM is verified by appropriate simulations and experiments.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.3-5
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• 2005

Vessel boundary detection and modeling is a difficult but a necessary task in analyzing the mechanics of inflammation and the structure of the microvasculature. In this paper we present a method of analyzing the structure by means of an active contour model(using GVF Snake) for vessel boundary detection and 3D reconstruction. For this purpose we used a virtual vessel model and produced a phantom model. From these phantom images we obtained the contours of the vessel by GVF Snake and then reconstructed a 3D structure by using the coordinates of snakes.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.321-329
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• 1999

Moving Object segmentation extracts an interested moving object on a consecutive image frames, and has been used for factory automation, autonomous navigation, video surveillance, and VOP(Video Object Plane) detection in a MPEG-4 method. This paper proposes new segmentation method using difference images are calculated with three consecutive input image frames, and used to calculate both coarse object area(AI) and it's movement area(OI). An AI is extracted by removing background using background area projection(BAP). Missing parts in the AI is recovered with help of the OI. Boundary information of the OI confines missing parts of the object and gives inital curves for active contour optimization. The optimized contours in addition to the AI make the boundaries of the moving object. Experimental results of a fast moving object on a complex background scene are included.