• Journal of Korea Game Society
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• v.17 no.5
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• pp.113-122
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• 2017

The location of the objects that make up a game can be an element of immersion for players. repeatedly appearing at the same position, the fun may be reduced, and as the play time elapses, the players will feel the game's fun as they appear in a larger area than at the beginning of the game play. This paper is a study to find out the location of objects according to the passage of time and to see how players controlled these objects. First, foreground images are extracted and accumulated using OpenCV programming language. The accumulated result is displayed as a heat map image. Second, the mouse movement area is detected using the mouse tracking program and compared with the heat map image, so that the screen area in which the player is interested can be known.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.687-696
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• 2014

This paper presents a semantic object extraction method using user's stroke input, color, and depth information. It is supposed that a semantically meaningful object is surrounded with a few strokes from a user, and has similar depths all over the object. In the proposed method, deciding the region of interest (ROI) is based on the stroke input, and the semantically meaningful object is extracted by using color and depth information. Specifically, the proposed method consists of two steps. The first step is over-segmentation inside the ROI using color and depth information. The second step is semantically meaningful object extraction where over-segmented regions are classified into the object region and the background region according to the depth of each region. In the over-segmentation step, we propose a new marker extraction method where there are two propositions, i.e. an adaptive thresholding scheme to maximize the number of the segmented regions and an adaptive weighting scheme for color and depth components in computation of the morphological gradients that is required in the marker extraction. In the semantically meaningful object extraction, we classify over-segmented regions into the object region and the background region in order of the boundary regions to the inner regions, the average depth of each region being compared to the average depth of all regions classified into the object region. In experimental results, we demonstrate that the proposed method yields reasonable object extraction results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1240-1250
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• 2010

In this paper, an eye tracking method is presented by using on iterated spatial moment adapting weighted gray level that can accurately detect and track user's eyes under the complicated background. The region of face is detected by using Haar-like feature before extracting region of eyes to minimize an region of interest from the input picture of CCD camera. And the region of eyes is detected by using eigeneye based on the eigenface of Principal component analysis. Also, feature points of eyes are detected from darkest part in the region of eyes. The tracking of eyes is achieved correctly by using iterated spatial moment adapting weighted gray level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.198-201
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• 2009

In this paper, an eye tracking method is presented by using on iterated spatial moment adapting weighted gray level that can accurately detect and track user's eyes under the complicated background. The region of face is detected by using Haar-like feature before extracting region of eyes to minimize an region of interest from the input picture of CCD camera. And the region of eyes is detected by using eigeneye based on the eigenface of Principal component analysis. And then feature points of eyes are detected from darkest part in the region of eyes. The tracking of eyes is achieved correctly by using iterated spatial moment adapting weighted gray level.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.547-551
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• 2009

In recent years, a film restoration has gained increasing attention by many researchers, to emergence of variety multimedia and to importance of video preservation. Blotch is the most frequent degradation in old film. This paper presents a blotch detection method using color and shape feature. The proposed method is two major modules: a SROD detector using impulsive feature and NN-based detector using shape feature. To assess the validity of the proposed method, the experiments have been performed on several old films.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.310-313
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• 2003

최근 들어 립리딩은 멀티모달 인터페이스 기술의 응용분야에서 많은 관심을 모으고 있다. 동적영상을 이용한 립리딩 시스템에서 해결해야 할 주된 문제점은 상황 변화에 독립적으로 얼굴 영역과 입술 영역을 추출하고 오프라인이 아닌 실시간으로 입력된 입술 영상의 인식을 처리하여 립리딩의 사용도를 높이는 것이다. 본 논문에서는 사용자가 쉽게 사용할 수 있는 PC카메라를 사용하여 영상을 입력받아 학습과 인식을 실시간으로 처리하는 립리딩 시스템을 구현하였다. 본 논문에서는 움직임이 있는 화자의 얼굴영역과 입술영역을 컬러, 조명등의 변화에 독립적으로 추출하기 위해 HSI모델을 이용하였다. 입력 영상에서 일정한 크기의 영역에 대한 색도 히스토그램 모델을 만들어 색도 영상에 적용함으로써 얼굴영역의 확률 분포를 구하였고, Mean-Shift Algorithm을 이용하여 얼굴영역의 검출과 추적을 하였다. 특징 점 추출에는 이미지 기반 방법인 PCA 기법을 이용하였고, HMM 기반 패턴 인식을 사용하여 실시간으로 실험영상데이터에 대한 학습과 인식을 수행할 수 있었다.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.150-159
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• 2005

With the increase of interest in ubiquitous computing, image code is attracting attention in various areas. Image code is important in ubiquitous computing in that it can complement or replace RFID (radio frequency identification) in quite a few areas as well as it is more economical. However, because of the difficulty in reading precise colors due to the severe distortion of colors, its application is quite restricted by far. In this paper, we present an efficient method of image code recognition including automatically locating the image code using the hue and saturation values. In our experiments, we use an image code whose design seems most practical among currently commercialized ones. This image code uses six safe colors, i.e., R, G, B, C, M, and Y. We tested for 72 true-color field images with the size of $2464{\times}1632$ pixels. With the color calibration based on the histogram, the localization accuracy was about 96%, and the accuracy of color classification for localized codes was about 91.28%. It took approximately 5 seconds to locate and recognize the image code on a PC with 2 GHz P4 CPU.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.189-198
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• 2024

Lipreading is one of the important parts of speech recognition, and several studies have been conducted to improve the performance of lipreading in lipreading systems for speech recognition. Recent studies have used method to modify the model architecture of lipreading system to improve recognition performance. Unlike previous research that improve recognition performance by modifying model architecture, we aim to improve recognition performance without any change in model architecture. In order to improve the recognition performance without modifying the model architecture, we refer to the cues used in human lipreading and set other regions such as chin and cheeks as regions of interest along with the lip region, which is the existing region of interest of lipreading systems, and compare the recognition rate of each region of interest to propose the highest performing region of interest In addition, assuming that the difference in normalization results caused by the difference in interpolation method during the process of normalizing the size of the region of interest affects the recognition performance, we interpolate the same region of interest using nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, and compare the recognition rate of each interpolation method to propose the best performing interpolation method. Each region of interest was detected by training an object detection neural network, and dynamic time warping templates were generated by normalizing each region of interest, extracting and combining features, and mapping the dimensionality reduction of the combined features into a low-dimensional space. The recognition rate was evaluated by comparing the distance between the generated dynamic time warping templates and the data mapped to the low-dimensional space. In the comparison of regions of interest, the result of the region of interest containing only the lip region showed an average recognition rate of 97.36%, which is 3.44% higher than the average recognition rate of 93.92% in the previous study, and in the comparison of interpolation methods, the bilinear interpolation method performed 97.36%, which is 14.65% higher than the nearest neighbor interpolation method and 5.55% higher than the bicubic interpolation method. The code used in this study can be found a https://github.com/haraisi2/Lipreading-Systems.

• Journal of Digital Contents Society
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• v.16 no.4
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• pp.615-622
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• 2015

Recently virtual advertising is located in an important area of interest in the TV market by convenience of application and reduction of cost. The methods of inserting a virtual advertising in broadcasting are Up-link that method insert the image through the production equipment of the broadcasting station and dispatch equipment and technical personnel in the shooting and Down-streaming that method insert a virtual image automatically in relay video using image processing technology. In recent years, the image processing technology is an important research area in the virtual advertising area for automatically insertion of advertising images. In this paper, we propose the method to extract less-informative region in sports video using image processing. The proposed method extracts less-Informative region through rectangle detection of Hough transform and analysis of color histogram distribution.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.3
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• pp.165-178
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• 2007

The recent progress in multimedia signal processing and transmission technologies has contributed to the extensive use of multimedia devices to watch sports games with small LCD panel. However, the most of video sequences are captured for normal viewing on standard TV or HDTV, for cost reasons, merely resized and delivered without additional editing. This may give the small-display-viewers uncomfortable experiences in understanding what is happening in a scene. For instance, in a soccer video sequence taken by a long-shot camera techniques, the tiny objects (e.g., soccer ball and players) may not be clearly viewed on the small LCD panel. Moreover, it is also difficult to recognize the contents of the scorebox which contains the elapsed time and scores. This renuires intelligent display technique to provide small-display-viewers with better experience. To this end, one of the key technologies is to determine region of interest (ROI) and display the magnified ROI on the screen, where ROI is a part of the scene that viewers pay more attention to than other regions. Examples include a region surrounding a ball in long-shot and a scorebox located in the comer of each frame. In this paper, we propose a scheme for raising viewing experiences of multimedia mobile device users. Instead of taking generic approaches utilizing visually salient features for extraction of ROI in a scene, we take domain-specific approach to exploit unique attributes of the soccer video. The proposed scheme consists of two modules: ROI determination and scorebox extraction. The experimental results show that the proposed scheme offers useful tools for intelligent video display on multimedia mobile devices.