• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.103-112
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• 2008

Image-based motion capture technology is often used in making realistic computer animation. In this paper we try to implement image-based motion rendering by fixing a camera to a PC. Existing image-based rendering algorithms have disadvantages of high computational burden or low accuracy. The former disadvantage causes too long making-time of an animation. The latter disadvantage degrades reality in making realistic animation. To compensate for those disadvantages of the existing approaches, this paper presents an image-based motion rendering algorithm with low computational load and high estimation accuracy. In the proposed approach, an incremental motion rendering algorithm with low computational load is analyzed in the respect of optimal control theory and revised so that its estimation accuracy is enhanced. If we apply this proposed approach to optic motion capture systems, we can obtain additional advantages that motion capture can be performed without any markers, and with low cost in the respect of equipments and spaces.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1551-1560
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• 1997

This study is devoted to the detection of the 3-dimensional point obstacles on the plane by using accumulated scan line images. The proposed accumulating only one scan line allow to process image at real time. And the change of motion of the feature in image is small because of the short time between image frames, so it does not take much time to track features. To obtain recursive optimal obstacles position and robot motion along to the motion of camera, Kalman filter algorithm is used. After using Kalman filter in case of the fixed environment, 3-dimensional obstacles point map is obtained. The position and motion of moving obstacles can also be obtained by pre-segmentation. Finally, to solve the stereo ambiguity problem from multiple matches, the camera motion is actively used to discard mis-matched features. To get relative distance of obstacles from camera, parallel stereo camera setup is used. In order to evaluate the proposed algorithm, experiments are carried out by a small test vehicle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.366-385
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• 2013

In this paper, we propose a compressed sensing (CS) based Wyner-Ziv (WZ) codec using motion-aligned auto regressive model (MAAR) based side information (SI) extrapolation to improve the compression performance of low-delay distributed video coding (DVC). In the CS based WZ codec, the WZ frame is divided into small blocks and CS measurements of each block are acquired at the encoder, and a specific CS reconstruction algorithm is proposed to correct errors in the SI using CS measurements at the decoder. In order to generate high quality SI, a MAAR model is introduced to improve the inaccurate motion field in auto regressive (AR) model, and the Tikhonov regularization on MAAR coefficients and overlapped block based interpolation are performed to reduce block effects and errors from over-fitting. Simulation experiments show that our proposed CS based WZ codec associated with MAAR based SI generation achieves better results compared to other SI extrapolation methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.10-18
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• 2010

This paper proposes an image stabilization algorithm for close watching UAV(Unmanned Aerial Vehicle) using motion separation and stabilization mode. The motion of UAV is composed of its actual navigating motion and unwanted vibrating motion so that image sequences obtained from UAV are shaken randomly. In order to stabilize these images we separate the vibrating motion component from UAV motion and remove the effect caused by it from image sequences. In the proposed algorithm the motion and global intensity change of two consecutive images are modeled with 6 motion parameters and 2 intensity change parameters respectively. These modeled parameters are estimated by non-linear least square method based on Gauss-Newton algorithm. The vibrating motion component is separated from the estimated motion using IIR filtering and the geometric deformation caused by it is removed from image sequences. In order to apply the proposed method to real aerial image sequences with many abrupt changes of camera view, we proposed a stabilizing method using two different modes named as stabilizing and non-stabilizing mode. Experimental results show that the accuracy of motion estimation is 99% and the efficiency of removing the vibrating motion component is 90%. We apply the proposed method to real aerial image sequences and verified its stabilizing performance.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.47-51
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• 2005

Using satellite images, an optimal solution to water motion has been presented in this study. Since temperature patterns are suitable tracers in water motion, Sea Surface Temperature (SST) images of Caspian Sea taken by MODIS sensor on board Terra satellite have been used in this study. Two daily SST images with 24 hours time interval are used as input data. Computation of templates correspondence between pairs of images is crucial within motion algorithms using non-rigid body objects. Image matching methods have been applied to estimate water body motion within the two SST images. The least squares matching technique, as a flexible technique for most data matching problems, offers an optimal spatial solution for the motion estimation. The algorithm allows for simultaneous local radiometric correction and local geometrical image orientation estimation. Actually, the correspondence between the two image templates is modeled both geometrically and radiometrically. Geometric component of the model includes six geometric transformation parameters and radiometric component of the model includes two radiometric transformation parameters. Using the algorithm, the parameters are automatically corrected, optimized and assessed iteratively by the least squares algorithm. The method used in this study, has presented more efficient and robust solution compared to the traditional motion estimation schemes.

• Journal of Broadcast Engineering
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• v.3 no.1
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• pp.50-60
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• 1998

This paper addresses a problem of extraction of parameteric motion estimation and structural motion segmentation for compact image sequence representation and object-based generic video coding. In order to extract meaningful motion structure from image sequences, a direct parameteric motion estimation based on a pre-segmentation is proposed. The pre-segmentation which considers the motion of the moving objects is canied out based on probabilistic clustering with mixture models using optical flow and image intensities. Parametric motion segmentation can be obtained by iterated estimation of motion model parameters and region reassignment according to a criterion using Gauss-Newton iterative optimization algorithm. The efficiency of the proposed methoo is verified with computer simulation using elF real image sequences.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.999-1002
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• 2003

In this study, embodied supervisory system that apply motion detection technique to small web camera and detects watch picture. Motion detection technique that use pixel value of car image that use in existing need memory to store background image. Also, there is sensitive shortcoming at increase of execution time by data process of pixel unit and noise. Suggested technique that compare extracting motion information by block unit to do to have complexion that solve this shortcoming and is strong at noise. Because motion information by block compares block characteristic value of image without need frame memory, store characteristic cost by block of image. Also, can get effect that reduce influence about noise and is less sensitive to flicker etc.. of camera more than motion detection that use pixel value in process that find characteristic value by block unit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.74-79
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• 2004

In this study, embodied supervisory system that apply motion detection technique to small web camera and detects watch picture. Motion detection technique that use pixel value of car image that use in existing need memory to store background image. Also, there is sensitive shortcoming at increase of execution time by data process of pixel unit and noise. Suggested technique that compare extracting motion information by block unit to do to have complexion that solve this shortcoming and is strong at noise. Because motion information by block compares block characteristic value of image without need frame memory, store characteristic cost by block of image. Also, can get effect that reduce influence about noise and is less sensitive to flicker etc.. of camera more than motion detection that use pixel value in process that find characteristic value by block unit.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.631-634
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• 1999

In this work, a new algorithm for canceling MRI artifact in the image plane is presented. In the conventional approach, the motions in the X(readout) direction and Y(the phase encoding) direction are estimated simultaneously. However, the feature of each X and Y directional motion is different. First, we notice that the X directional motion corresponds to a shift of the X directional spectrum of the MRI signal, and the non zero area of the spectrum just corresponds to X axis projected area of the density function. So the motion is estimated by tracing the edges of the spectrum, and the X directional motion is canceled by shifting the spectrum in inverse direction. Next, the Y directional motion is canceled using a new constraint, with which the motion component and the true image component can be separated. This algorithm is shown to be effective by simulations.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1075-1078
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• 1999

In this study, a new algorithm for canceling MRI artifacts through the translational motion of image plane is presented. Bloating is often makes problems in a clinical diagnosis. Assuming that the head moves up and down due to breathing, rigid translational motions in only y(phase encoding axis) direction is treated. First, we notice that the x directional motion corresponds to a shift of the x directional spectrum of the MRI signal, and the non zero area of the spectrum just corresponds to x axis projected area of the density function. So the motion is estimated by tracing the edges of the spectrum, and the x directional motion is canceled by shifting the spectrum in inverse direction. Next, the y directional motion is canceled using a new constraint, with which the motion component and the true image component can be separated. Finally, the effectiveness of this algorithm is shown by using a phantom with simulated motions.