• Journal of Sensor Science and Technology
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• v.13 no.2
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• pp.144-151
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• 2004

In this paper, we propose an active stereo surveillance system with human-like convergence function. The proposed system uses a bottom-up saliency map model with the human-like selective attention visual function to select an interesting region in each camera. and this system compares the landmarks whether the selective region in each camera finds a same region. If the left and right cameras successfully find a same landmarks, the implemented vision system focuses on the landmark. Using the motor encoder information, we can automatically obtain the depth information and resultantly construct a depth map using the depth information. Computer simulation and experimental results show that the proposed convergence method is very effective to implement the active stereo surveillance system.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2200-2202
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• 1998

Autonomous mobile robot provide many functions such as sensing, processing, and driving. For more intelligent jobs, more intelligent functions are to be added and the existing functions may be updated. To execute a job autonomous mobile robot has a information of surrounding environment. So, robot uses sonar sensor, vision sensor and so on. Obtained sensor information is used map generation. This paper is focused on map generation using stereo vision system.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.716-725
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• 2007

In this paper we describe a motion tracking algorithm for 3D human animation using stereo vision system. This allows us to extract the motion data of the end effectors of human body by following the movement through segmentation process in HIS or RGB color model, and then blob analysis is used to detect robust shape. When two hands or two foots are crossed at any position and become disjointed, an adaptive algorithm is presented to recognize whether it is left or right one. And the real motion is the 3-D coordinate motion. A mono image data is a data of 2D coordinate. This data doesn't acquire distance from a camera. By stereo vision like human vision, we can acquire a data of 3D motion such as left, right motion from bottom and distance of objects from camera. This requests a depth value including x axis and y axis coordinate in mono image for transforming 3D coordinate. This depth value(z axis) is calculated by disparity of stereo vision by using only end-effectors of images. The position of the inner joints is calculated and 3D character can be visualized using inverse kinematics.

• ETRI Journal
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• v.37 no.4
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• pp.752-765
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• 2015

We propose a novel post-processing algorithm and its very-large-scale integration architecture that simultaneously uses the passive and active stereo vision information to improve the reliability of the three-dimensional disparity in a hybrid stereo vision system. The proposed architecture consists of four steps - left-right consistency checking, semi-2D hole filling, a tiny adaptive variance checking, and a 2D weighted median filter. The experimental results show that the error rate of the proposed algorithm (5.77%) is less than that of a raw disparity (10.12%) for a real-world camera image having a $1,280{\times}720$ resolution and maximum disparity of 256. Moreover, for the famous Middlebury stereo image sets, the proposed algorithm's error rate (8.30%) is also less than that of the raw disparity (13.7%). The proposed architecture is implemented on a single commercial field-programmable gate array using only 13.01% of slice resources, which achieves a rate of 60 fps for $1,280{\times}720$ stereo images with a disparity range of 256.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.848-853
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• 2005

3D geometric modeling of an object of interest has been intensively investigated in many fields including CAD/CAM and computer graphics. Traditionally, CAD and geometric modeling tools are widely used to create geometric models that have nearly the same shape of 3D real objects or satisfy designers intent. Recently, with the help of the reverse engineering (RE) technology, we can easily acquire 3D point data from the objects and create 3D geometric models that perfectly fit the scanned data more easily and fast. In this paper, we present 3D geometric model generation based on a stereo vision system (SVS) using random pattern projection. A triangular mesh is considered as the resulting geometric model. In order to obtain reasonable results with the SVS-based geometric model generation, we deal with many steps including camera calibration, stereo matching, scanning from multiple views, noise handling, registration, and triangular mesh generation. To acquire reliable stere matching, we project random patterns onto the object. With experiments using various random patterns, we propose several tips helpful for the quality of the results. Some examples are given to show their usefulness.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.99.5-99
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• 2002

$\textbullet$ 3-D object tracking framework $\textbullet$ Using fast stereo vision system for range image $\textbullet$ Using CONDENSATION algorithm to tracking object $\textbullet$ For recognizing object, superquardrics model is used $\textbullet$ Our target object is like coils in steel works

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.610-615
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• 2005

Visual servoing is the fusion of results from many elemental areas including high-speed image processing, kinematics, dynamics, control theory, and real-time computing. It has much in common with research into active vision and structure from motion, but is quite different from the often described use of vision in hierarchical task-level robot control systems. We present a new approach to visual feedback control using image-based visual servoing with the stereo vision in this paper. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using a binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only at around a desired location but also at the other locations. The suggested technique can guide a robot manipulator to the desired location without giving such priori knowledge as the relative distance to the desired location or the model of an object even if the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by the simulation and experimental results and compared with the case of conventional method for dual-arm robot made in Samsung Electronics Co., Ltd.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.03a
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• pp.207-212
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• 1997

In estimating the formability of sheet metal, the stereo vision system contributes the accuracy of strain of sheet metal, the convenience in measuring the strain of sheet metal, and the handiness in preparing the forming limit diagram by calculating the 3D values and strain of sheet metal. The algorithm has been developed so that the 3D-coordinate values of sheet metal could be calculated by image processing which is composed of camera calibration, and the stereo matching of images in two viewpoints. By comparing with experiments, the possibility and the convenience of algorithm has been verified, which could calculate the 3D-coordinate values of sheet metal automatically by using the preprocessing of the original image of sheet metal, which had the noise before adjusting the camera calibration and the stereo matching algorithm.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1354-1359
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• 2008

In this paper, we propose a vision based passenger monitoring system for passenger's safety in railway station. Since 2005, Korea Railroad Research Institute (KRRI) has developed a vision based monitoring system, funded by Korean government, for passenger's safety in railway station. The proposed system uses various types of sensors, such as, stereo camera, thermal-camera and infrared sensor, in order to detects danger situations in platform area. Especially, detection process of the system exploits the stereo vision algorithm to improve detection accuracy. The paper describes the overall system configuration and proposed detection algorithm, and then verifies the system performance with extensive experimental results in a real station environment.

• ETRI Journal
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• v.32 no.5
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• pp.750-760
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• 2010

We propose a homology between thermodynamic systems and images for the treatment of time-varying imagery. A physical system colder than its surroundings absorbs heat from the surroundings. Furthermore, the absorbed heat increases the entropy of the system, which is closely related to its disorder as given by the definition of Clausius and Boltzmann. Because pixels of an image are viewed as a state of lattice-like molecules in a thermodynamic system, the task of reckoning the entropy variations of pixels is similar to estimating their degrees of disorder. We apply this homology to the uncalibrated stereo matching problem. The absence of calibrations alleviates user efforts to install stereo cameras and enables users to freely modify the composition of the cameras. The proposed method is also robust to differences in brightness, white balancing, and even focusing between stereo image pairs. These peculiarities enable users to estimate the depths of interesting objects in practical applications without much effort in order to set and maintain a stereo vision setup. Users can consequently utilize two webcams as a stereo camera.