• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.5
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• pp.659-664
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• 2013

It is necessary to develop an efficient MVD coding scheme to improve the video coding performance. In this paper, combined codeword and joint codeword are suggested from analyses on statistical distributions of MVD according to the quantization steps and the conventional codeword structure. Based on these codewords, we propose new MVD coding scheme where one of the suggested codewords is employed to encode the MVD according to the coding environment. Simulation results show that the proposed scheme enhances the coding performance without the quality degradation.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.90-97
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• 2013

Recently, intelligent transportation system based on image processing has been developed. In this paper, we propose a collision detection algorithm based on the analysis of motion vectors and the staying periods of vehicles in intersections. Objects in the region of interest are extracted from the subtraction image between background images based on Gaussian mixture model and input images. Collisions and traffic jams are detected by analysing measured motion vectors of vehicles and their staying periods in intersections. Experiments are performed on video sequences actually recoded at intersections. Correct detection rate and false alarm rate are 85.7% and 7.7%, respectively.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.379-385
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• 2007

관성 센서는 외부 장치의 도움 없이 3차원 공간상에서 움직임 측정이 가능하다. 최근 MEMS 기술의 발달로 소형 저가 관성 센서(가속도 센서 혹은 각속도 센서) 제작이 가능해져 관성 센서를 소형 휴대 기기에 내장하여 사용자의 움직임을 감지하거나 의도 파악하는 연구가 진행되고 있다. 본 연구에서는 관성 센서가 내장된 휴대 기기를 이용하여 3차원 공간상에서 6가지 위치에 따라서 각기 다른 6가지 소리를 발생하는 가상의 멀티 타악기 시스템을 제안한다. 즉, 휴대 기기를 상/하로 흔들면 가상 타악기의 타점 위치에 왔을 때 비트 음을 발생하고, 6개의 다른 위치를 구분하여 다른 타점의 위치에서 휴대 기기를 흔들면 각각 그 위치와 미리 지정된 소리가 발생하도록 하였다. 이러한 가상의 멀티 타악기 시스템을 위해서 3차원 공간상에서 실시간으로 사용자의 움직임을 감지하고 휴대 기기의 위치를 파악하는 것이 필요하다. 저가의 관성 센서를 이용하여 사용자가 휴대 기기를 움직이는 동작이 있는 상황에서 실시간으로 휴대 기기의 위치를 추정하는 것은 쉽지 않지만 본 연구에서는 다양한 사용자의 움직임 동작 분석을 통하여 사용자가 가상의 멀티 타악기를 상/하로 흔드는 동작을 감지하고 다른 위치로 이동하는 동작을 구분하였다. 개발된 동작 감지 알고리즘과 위치 구분 알고리즘을 휴대 기기에 적용되어 실제로 가상의 타악기 시스템을 구현하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.361-369
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• 2002

In order to extract motion features from an input image acquired by a static CCD-camera in a restricted area, we need a robust algorithm to cope with noise sensitivity and condition change. In this paper, we proposed an efficient algorithm to extract and track motion features in a noisy environment or with sudden condition changes. We extract motion features by considering a change of neighborhood pixels when moving objects exist in a current frame with an initial background. To remove noise in moving regions, we used a morphological filter and extracted a motion of each object using 8-connected component labeling. Finally, we provide experimental results and statistical analysis with various conditions and models.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.284-288
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• 2010

Video surveillance is widely used in establishing the societal security network. In this paper, intrusion detection based on visual information acquired by static camera is proposed. Proposed approach uses background model constructed by approximated median filter(AMF) to find a foreground candidate, and detected object is calculated by analyzing motion information. Motion detection is determined by the relative size of 2D object in RGB space, finally, the threshold value for detecting object is determined by heuristic method. Experimental results showed that the performance of intrusion detection is better one when the spatio-temporal candidate informations change abruptly.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.96-105
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• 2004

The recovering 3D image from 2D requires the depth information for each picture element. The manual creation of those 3D models is time consuming and expensive. The goal in this paper is to estimate the relative depth information of every region from single view image with camera translation. The paper is based on the fact that the motion of every point within image which taken from camera translation depends on the depth. Motion vector using full-search motion estimation is compensated for camera rotation and zooming. We have developed a framework that estimates the average frame depth by analyzing motion vector and then calculates relative depth of region to average frame depth. Simulation results show that the depth of region belongs to a near or far object is consistent accord with relative depth that man recognizes.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.51-56
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• 2019

This paper proposes an improved heartbeat signal extraction method for ballistocardiography(BCG)-based heart-rate measurement on mobile environment. First, from a mobile facial video, a handshake-free head motion signal is extracted by tracking facial features and background features at the same time. Then, a novel signal periodicity computation method is proposed to accurately separate out the heartbeat signal from the head motion signal. The proposed method could robustly extract heartbeat signals from mobile facial videos, and enabled more accurate heart rate measurement (measurement errors were reduced by 3-4 bpm) compared to the existing method.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.279-286
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• 2021

The purpose of this study is to compare the predictive power of the Bagging and Boosting algorithm of ensemble method based on the motion information that occurs in woman handball matches and to analyze the availability of motion information. To this end, this study analyzed the predictive power of the result of 15 practice matches based on inertial motion by analyzing the predictive power of Random Forest and Adaboost algorithms. The results of the study are as follows. First, the prediction rate of the Random Forest algorithm was 66.9 ± 0.1%, and the prediction rate of the Adaboost algorithm was 65.6 ± 1.6%. Second, Random Forest predicted all of the winning results, but none of the losing results. On the other hand, the Adaboost algorithm shows 91.4% prediction of winning and 10.4% prediction of losing. Third, in the verification of the suitability of the algorithm, the Random Forest had no overfitting error, but Adaboost showed an overfitting error. Based on the results of this study, the availability of motion information is high when predicting sports events, and it was confirmed that the Random Forest algorithm was superior to the Adaboost algorithm.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.653-660
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• 2004

Object-oriented analysis-synthesis coding (OOASC) subdivides each image of a sequence into a number of moving objects and estimates and compensates the motion of each object. It employs a motion parameter technique for estimating motion information of each object. The motion parameter technique employing gradient operators requires a high computational load. The main objective of this paper is to present efficient motion parameter estimation techniques using the hierarchical structure in object-oriented analysis-synthesis coding. In order to achieve this goal, this paper proposes two algorithms : hybrid motion parameter estimation method (HMPEM) and adaptive motion parameter estimation method (AMPEM) using the hierarchical structure. HMPEM uses the proposed hierarchical structure, in which six or eight motion parameters are estimated by a parameter verification process in a low-resolution image, whose size is equal to one fourth of that of an original image. AMPEM uses the same hierarchical structure with the motion detection criterion that measures the amount of motion based on the temporal co-occurrence matrices for adaptive estimation of the motion parameters. This method is fast and easily implemented using parallel processing techniques. Theoretical analysis and computer simulation show that the peak signal to noise ratio (PSNR) of the image reconstructed by the proposed method lies between those of images reconstructed by the conventional 6- and 8-parameter estimation methods with a greatly reduced computational load by a factor of about four.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.500-507
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• 2021

The virtual reality industry has an opportunity to take another leap forward with the surge in demand for non-face-to-face content and interest in the metaverse after Covid-19. Therefore, in order to popularize virtual reality content along with this trend, high-quality content production and storytelling research suitable for the characteristics of virtual reality should be continuously conducted. In order for content to which virtual reality characteristics are applied to be effectively produced through user feedback, a quantitative index that can evaluate the content is needed. In this study, the process of viewing virtual reality contents was analyzed and head movement was set as a quantitative indicator. Afterwards, the experimenter watched five animations and analyzed the correlation between recorded head movement information and immersion. As a result of the analysis, high immersion was shown when the head movement speed was relatively slow, and it was found that the head movement speed can be used significantly as an index indicating the degree of content immersion. The result derived in this way can be used as a quantitative indicator that can verify the validity of the storytelling method applied after the prototype is produced when the creator creates virtual reality content. This method can improve the quality of content by quickly identifying the problems of the proposed storytelling method and suggesting a better method. This study aims to contribute to the production of high-quality virtual reality content and the popularization of virtual reality content as a basic research to analyze immersion based on the quantitative indicator of head movement speed.