• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.129-136
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• 1994

In this paper an adaptive moving method of the search region tracking the motion is proposed. The search region in BMA is determined by the capability of hardware implementation and the degree of motion. But once determined nothing can be changed during coding procedure. In this paper we predict the level of motion of the current block using motion vectors of previous frames without overhead information and change the location of the search region according to the level of the motion predicted. In short the proposed method can be archieved the dsirable effect such that the size of search region gets large when the motion is large. Results of experiments show that prediction efficiency has been improved by using adaptive moving method resulting in reduced prediction error in the blocks with large motion.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.110-114
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• 2015

This paper reports a novel object-detection technique in video sequences. The proposed algorithm consists of detection of objects in illuminated and occluded videos by using object features and a neural network technique. It consists of two functional modules: region-based object feature extraction and continuous detection of objects in video sequences with region features. This scheme is proposed as an enhancement of the Lowe's scale-invariant feature transform (SIFT) object detection method. This technique solved the high computation time problem of feature generation in the SIFT method. The improvement is achieved by region-based feature classification in the objects to be detected; optimal neural network-based feature reduction is presented in order to reduce the object region feature dataset with winner pixel estimation between the video frames of the video sequence. Simulation results show that the proposed scheme achieves better overall performance than other object detection techniques, and region-based feature detection is faster in comparison to other recent techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.3
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• pp.469-480
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• 1997

For moving image coding, the variable size of region coding based on local motion is more efficient than fixed size of region coding. It can be applied well to complex motions and is more stable for wide motions because images are segmented according to local motions. In this paper, new image coding method using the segmentation of motion vectors is proposed. First, motion vector field is smoothed by filtering and segmented by smoothed motion vectors. The region growing method is used for decomposition of regions, and merging of regions is decided by motion vector and prediction errors of the region. Edge of regions is excluded because of the correlation of image, and neighbor motion vectors are used evaluation of current block and construction of region. The results of computer simulation show the proposed method is superior than the existing methods in aspect of coding efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1755-1766
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• 1999

A region-based video codec based on the H.263+ standard is examined and its associated novel rate control scheme is proposed in this work. The region-based coding scheme is a hybrid method that consists of the traditional block DCT coding and the object-based coding. Basically, we adopt H.263+ as the platform, and develop a fast macroblock-based segmentation method to implement the region-based video codec. The proposed rate control solution includes rate control in three levels: encoding frame selection, frame-layer rate control and macroblock-layer rate control. The goal is to enhance the visual quality of decoded frames at low bit rates. The efficiency of proposed rate control scheme applied to the region-based video codes is demonstrated via several typical test sequences.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.721-723
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• 2004

A trust-region method is a quite attractive optimization technique. It is, in general, faster than the steepest descent method and is free of a learning rate unlike the gradient-based methods. In addition to its convergence property (between linear and quadratic convergence), ifs stability is always guaranteed, in contrast to the Newton's method. In this paper, we present an efficient implementation of the maximum likelihood independent component analysis (ICA) using the trust-region method, which leads to trust-region-based ICA (TR-ICA) algorithms. The useful behavior of our TR-ICA algorithms is confimed through numerical experimental results.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.156-165
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• 2021

In this paper, we propose an histogram weighted centroid based Siamese region proposal network for object tracking. The original Siamese region proposal network uses two identical artificial neural networks which take two different images as the inputs and decide whether the same object exist in both input images based on a similarity measure. However, as the Siamese network is pre-trained offline, it experiences many difficulties in the adaptation to various online environments. Therefore, in this paper we propose to incorporate the histogram weighted centroid feature into the Siamese network method to enhance the accuracy of the object tracking. The proposed method uses both the histogram information and the weighted centroid location of the top 10 color regions to decide which of the proposed region should become the next predicted object region.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1566-1576
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• 2007

Camera pose information from 2D face image is very important for making virtual 3D face model synchronize with the real face. It is also very important for any other uses such as: human computer interface, 3D object estimation, automatic camera control etc. In this paper, we have presented a camera position determination algorithm from a single 2D face image using the relationship between mouth position information and face region boundary information. Our algorithm first corrects the color bias by a lighting compensation algorithm, then we nonlinearly transformed the image into $YC_bC_r$ color space and use the visible chrominance feature of face in this color space to detect human face region. And then for face candidate, use the nearly reversed relationship information between $C_b\;and\;C_r$ cluster of face feature to detect mouth position. And then we use the geometrical relationship between mouth position information and face region boundary information to determine rotation angles in both x-axis and y-axis of camera position and use the relationship between face region size information and Camera-Face distance information to determine the camera-face distance. Experimental results demonstrate the validity of our algorithm and the correct determination rate is accredited for applying it into practice.

• International Commerce and Information Review
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• v.1 no.1
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• pp.3-24
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• 2008

This paper examines the corporate parent effect on the diversification strategies of triad and Asian subsidiaries in the ASEAN region. I find that triad subsidiaries tend to participate in high technology intensive industries, and are more likely to diversify. In addition, I also find that the subsidiary diversification strategy is significantly affected by the number of affiliations under the same corporate parent that perform the same or different activities in the region. These results shed light on the influence of corporate parent on subsidiary-level strategy and the role of the subsidiary within an economically integrated region. Various implications are discussed.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.4
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• pp.587-592
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• 2004

Pixel classification is one of basic issues of image processing. The general characteristics of the pixels belonging to various classes are discussed and the radical principles of pixel classification are given. At the same time, a pixel classification scheme based on image information scales is proposed. The proposed method is overcome that computation amount become greater and contents easily get turned. And image directional scales has excellent anti-noise performance. In the result of experiment. good efficiency is showed compare with other methods.

• Information and Communications Magazine
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• v.19 no.9
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• pp.31-42
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• 2002

CRL (Communications Research Laboratory, Independent Administrative Institution, Japan) is developing ITS wireless communication technologies in millimeter-wave frequency region. Technologies are categorized for inter-vehicle communications (IVC) and road-vehicle communications (RVC). In this paper, system concepts and the experimental facilities are introduced. The experimental facility for inter-vehicle communications is gotten ready in 60 GHz frequency region and the experimental system for road-vehicle communications is based on RoF (Radio on Fiber) technology in 36-37GHz frequency region.