• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.411-417
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• 2007

The rate control is an essential component in video coding to provide better quality under given coding constraints, such as channel capacity, frame rates, etc. In general, source data cannot be described as a single distribution in a video coding, hence it can cause an exhaustive approximation problem. It drops a coding efficiency under weak channel environments, such as mobile communications. In this paper, we design a new quantization parameter decision model that is based on a rate-distortion function of generalized Gaussian distribution. In order to adaptively express various source data distribution, we decide a shape parameter by observing a ratio of samples, which have a small value. For experiment, the proposed algorithm is implemented into H.264/AVC video codec, and its performance is compared with that of MPEG-2 TM5, H.263 TMN8 rate control algorithm. As shown in simulation results, the proposed algorithm provides an improved quality rather than previous algorithms and generates the number of bits closed to the target bits.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.10 s.101
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• pp.1010-1019
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• 2005

In this paper, we used neural network technique to model memory effects of RF power amplifier which is fed by two-tone input signals. The memory effects in power amplifier were identified by observing the unsymmetrical distribution of IMD(Inter-Modulation Distortion) measurements with the change of tone spacings and power levels. Different asymmetries of IMD were also found at different center frequencies. We applied TDNN technique to model LDMOS power amplifier based on two tone IMD data, and the accuracy was very high compared to other modeling methods such as the(memoryless) adaptive modeling method.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.2
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• pp.125-130
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• 2012

The nematode Caenorhabditis elegans is a widely used model organism in biological research. Thanks to the availability of well-established knowledge about its neural connectivity, a wide range of studies have been attempted to uncover the relationship between behaviors and the responsible neurons. In our research, the adaptive behavior of C. elegans in solid environments with different surface rigidities is investigated, where the worm adapts to different mechanical stiffnesses by modulating its crawling waveform. The amplitude and wavelength of the crawling waveform decrease as the environment becomes more rigid. Interestingly, the mechanosensation-defective mutant shows different responses to the surface rigidity compared to those of the wild-type worm. To explain the adaptation process in mechanically different environments, we suggest a plausible neural circuit model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.229-240
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• 2012

The development of multimedia applications followed by development of high-speed networks has improved the performance of mobile devices with high transfer speed broadband. Mobile internet access has made possible seamless indoor and outdoor mobile multicast services. Multicasting services are used to support efficient group communications. However, mobile multicasting services have two constraints: tunnel convergence and handover latency. Many protocols and handover methods have been proposed to address these problems. The inter-LMA optimized handover model for multicasting services has previously been proposed for PMIPv6-based networks. The proposed model removes the tunnel convergence issue and reduces router processing costs. It also makes possible the performance of fast handover operations with adaptive transmission mechanisms. In addition, the proposed scheme exhibits low packet delivery costs and handover latency in comparison with existing schemes, and ensures fast handover when moving the inter-LMA domain

• Journal of Broadcast Engineering
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• v.13 no.3
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• pp.299-309
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• 2008

In this paper, we propose an algorithm for object generation from model-based 3-dimensional multi-viewpoint images using OpenGL rendering. In the first step, we preprocess a depth map image in order to get a three-dimensional coordinate which is sampled as a vertex information on OpenGL and has a z-value as depth information. Next, the Delaunay Triangulation algorithm is used to construct a polygon for texture-mapping using the vertex information. Finally, by mapping a texture image on the constructed polygon, we generate a viewpoint-adaptive object by calculating 3-dimensional coordinates on OpenGL.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.937-944
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• 2007

In this paper, we propose multiple human tracking with an moving stereo camera. The tracking process is based on mean shift algorithm which is using color information of the target. Color based tracking approach is invariant to translation and rotation of the target but, it has several problems. Because of mean shift uses color distribution, it is sensitive to color distribution of background and targets. In order to solve this problem, we combine color and depth information of target. Also, we build human body part model to handle occlusions and we have created adaptive box scale. As a result, the proposed method is simple and efficient to track multiple humans in real time.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.107-112
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• 2012

An active object tracking algorithm using Pan and Tilt camera based in the stepwise application of region and color information from realtime image sequences is proposed. To reduce environment noises in input sequences, Gaussian filtering is performed first. An image is divided into background and objects by using the adaptive Gaussian mixture model. Once the target object is detected, an initial search window close to an object region is set up and color information is extracted from the region. We track moving objects in realtime by using the CAMShift algorithm which enables to trace objects in active camera with the color information. The proper tracking is accomplished by controlling the amount of pan and tilt to be placed the center position of object into the middle of field of view. The experimental results show that the proposed method is more effective than the hand-operated window method.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.16 no.1
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• pp.31-49
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• 2012

In this paper, we propose a very efficient method which reconstructs the high resolution surface from a set of unorganized points. Our method is based on the level set method using adaptive octree. We start with the surface reconstruction model proposed in [20]. In [20], they introduced a very fast and efficient method which is different from the previous methods using the level set method. Most existing methods[21, 22] employed the time evolving process from an initial surface to point cloud. But in [20], they considered the surface reconstruction process as an elliptic problem in the narrow band including point cloud. So they could obtain very speedy method because they didn't have to limit the time evolution step by the finite speed of propagation. However, they implemented that model just on the uniform grid. So they still have the weakness that it needs so much memories because of being fulfilled only on the uniform grid. Their algorithm basically solves a large linear system of which size is the same as the number of the grid in a narrow band. Besides, it is not easy to make the width of band narrow enough since the decision of band width depends on the distribution of point data. After all, as far as it is implemented on the uniform grid, it is almost impossible to generate the surface on the high resolution because the memory requirement increases geometrically. We resolve it by adapting octree data structure[12, 11] to our problem and by introducing a new redistancing algorithm which is different from the existing one[19].

• Journal of Korea Game Society
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• v.6 no.1
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• pp.3-10
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• 2006

In computer games, the level design and balance of characters are the key features for developing interesting games. Level designers make decision to change the parameters and opponent behaviors in order to avoid the player getting extremely frustrated with the improper level. Generally, opponent behavior is defined by static script, this causes the games to have static difficulty level and static environment. Therefore, it is difficult to keep track of the user playing interest, because a player can easily adapt to changeless repetition. In this paper, we propose a dynamic scripting method that able to maintain the level designers' intention where user enjoys the game by adjusting the opponent behavior while playing the game. The player's countermeasure pattern for dynamic level design is modeled using a Gaussian Mixture Model (GMM). The proposed method is applied to a shooting game, and the experimental results maintain the degree of interest intended by the level designer.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.97-103
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• 2008

This study is to present a fainting motion recognizing method by using fish-eye lens images to sense emergency situations. The camera with fish-eye lens located at the center of the ceiling of the living room sends images, and then the foreground pixels are extracted by means of the adaptive background modeling method based on the Gaussian complex model, which is followed by tracing of outer points in the foreground pixel area and the elliptical mapping. During the elliptical tracing, the fish-eye lens images are converted to fluoroscope images. the size and location changes, and moving speed information are extracted to judge whether the movement, pause, and motion are similar to fainting motion. The results show that compared to using fish-eye lens image, extraction of the size and location changes. and moving speed by means of the conversed fluoroscope images has good recognition rates.