• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.265-272
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• 2009

In this paper, a simple optical method that uses an infrared(IR) cut filter is proposed to minimize variation of eye image by external infrared(IR) sources in a video based head mounted eye tracking system that is used in the field of sports. For this, the IR cut filter is attached to a head mount of the eye tracking system, and the camera with an IR LED is located between the IR cut filter and eye. In this structure, external IR is blocked by the IR cut filter, and the IR intensity on the eye can be controlled by the IR LED. Therefore, the illumination condition of the camera to capture the eye can be stable without being affected by external IR illuminations. To verify the proposed idea, variation of the eye image and intensity of the IR with/without the IR cut filter is measured under various illumination conditions. The measured data show that the IR cut filter method can block external IR effectively, and complex pupil detection algorithms can be replaced by a simple binarized method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1301-1307
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• 2001

Video retrieval system must offer representation frame list to do to do play from point that user wants. Representation frame list can get though cut detection point exactly. This paper dismembers frame to fixed block to cut detection point, and compare same block histogram cost of next time frame. If result that compare does not exceed thresold, detect next frame to cutting.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1955-1961
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• 1999

비디오 데이터는 비정형 데이터이고 정보의 양이 방대하기 때문에 내용기반 검색 방법이 필요하다. 비디오 데이터의 내용기반 검색을 위해서는 동영상 데이터의 색인이 필요한데, 일반적으로 비디오 색인을 하기 위한 시작점은 컷 검출이다. 본 논문에서는 컷 검출의 효율성을 향상시키기 위해서 컷 검출 과정 중 임계값이 동적으로 변화하는 동적 임계값 기법을 제안한다. 구현과 실험을 통하여 제안하는 방법이 기존의 방법보다 효율적임을 보였다. 6a A content-based search method is required for video which has an unformatted and huge size of data. The index technique is necessary for the content-based search of the video data. The first step of the video indexing is a cut detection. We propose a dynamic threshold method which changes a threshold value during the cut detection process. We demonstrate that the proposed method is more efficient than the existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2787-2800
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• 2022

The aging society increases emergency situations of the elderly living alone and a variety of social crimes. In order to prevent them, techniques to detect emergency situations through voice are actively researched. This study proposes CutPaste-based anomaly detection model using multi-scale feature extraction in time series streaming data. In the proposed method, an audio file is converted into a spectrogram. In this way, it is possible to use an algorithm for image data, such as CNN. After that, mutli-scale feature extraction is applied. Three images drawn from Adaptive Pooling layer that has different-sized kernels are merged. In consideration of various types of anomaly, including point anomaly, contextual anomaly, and collective anomaly, the limitations of a conventional anomaly model are improved. Finally, CutPaste-based anomaly detection is conducted. Since the model is trained through self-supervised learning, it is possible to detect a diversity of emergency situations as anomaly without labeling. Therefore, the proposed model overcomes the limitations of a conventional model that classifies only labelled emergency situations. Also, the proposed model is evaluated to have better performance than a conventional anomaly detection model.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.1-6
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• 2022

Scene change detection is an important topic because of the wide and growing range of its applications. Streaming services from many providers are increasing their capacity which causes the industry growth. The method for the scene change detection is described here and compared with the State-of-the-Art methods over the Open Video Scene Detection (OVSD) - an open dataset of Creative Commons licensed videos freely available for download and use to evaluate video scene detection algorithms. The proposed method is based on scene analysis using threshold values and smooth scene changes. A comparison of the presented method was conducted in this research. The obtained results demonstrated the high efficiency of the scene cut localization method proposed by authors, because its efficiency measured in terms of precision, recall, accuracy, and F-metrics score exceeds the best previously known results.

• Journal of Internet Computing and Services
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• v.3 no.5
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• pp.51-62
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• 2002

The development of computer technology and the advancement of the technology of information and communications spread the technology of multimedia and increased the use of multimedia data with large capacity, Users can grasp the overall video data and they are able to play wanted video back. To grasp the overall video data it is necessary to offer the list of summarized video data information, In order to search video efficiently on index process of video data is essential and it is also indispensable skill, Therefore, this thesis suggested the effective method about the cut detection of frames which will become a basis of an index based on contents of video image data. This suggested method was detected as the unchanging pixel color intelligence value, classified into diagonal direction. Pixel value of color detected in each frame of video data is stored as A(i, j) matrix-i is the number of frames. j is an image height of frame. By using the stored pixel value as the method of sum of squared difference of color two frames I calculated a specified value difference between frames and detected cut quickly and exactly in case it is bigger than threshold value set in advance, To carry out on experiment on the cut detection of frames comprehensively, I experimented on many kinds of video. analyzing and comparing efficiency of the cut detection system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2401-2406
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• 1999

Various techniques extracting feature vectors have been studied for the cut detection in compressed video data. In case of using the histogram of occurrence of pixel's values as a feature vector, the precise detection of cuts would not be expected because of not considering the spatial correlation of pixels. And more sophisticated algorithms such as CCV(Color Coherent Vector) and Correlrogram tend to be used. Though these methods can be able to detect cuts rather precisely, they require much more processing time because of a enormous amount of computations. In this paper we propose a method of the cut detection using spatial correlation of DC values of luminance components in MPEG video sequence. This requires less processing time and also It can increase the rates of detecting the correct cuts by using advanced comparative method.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.211-217
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• 2012

Conventional GrabCut algorithm is semi-automatic algorithm that user must be set rectangle window surrounds the object. This paper studied automatic object detection to solve these problem by detecting salient region based on Human Visual System. Saliency map is computed using Lab color space which is based on color opposing theory of 'red-green' and 'blue-yellow'. Then Saliency Points are computed from the boundaries of Low-Frequency region that are extracted from Saliency Map. Finally, Rectangle windows are obtained from coordinate value of Saliency Points and these windows are used in GrabCut algorithm to extract objects. Through various experiments, the proposed algorithm computing rectangle windows of salient region and extracting objects has been proved.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.63-68
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• 2017

In this paper, we propose a bounding box prediction algorithm using multiple probability maps to improve object detection result of object detector. Although the performance of object detectors has been significantly improved, it is still not perfect due to technical problems and lack of learning data. Therefore, we use the result correction method to obtain more accurate object detection results. In the proposed algorithm, the preprocessed bounding box created as a result of object detection by the object detector is clustered in various form, and a conditional probability is given to each cluster to make multiple probability map. Finally, multiple probability map create new bounding box of object using morphological elements. Experiment results show that the newly predicted bounding box reduces the error in ground truth more than 45% on average compared to the previous bounding box.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1672-1686
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• 2013

In this paper, we propose a hybrid super-resolution algorithm robust to cut-change. Existing single-frame based super-resolution algorithms are usually fast, but quantity of information for interpolation is limited. Although the existing multi-frame based super-resolution algorithms generally robust to this problem, the performance of algorithm strongly depends on motions of input video. Furthemore at boundary of cut, applying of the algorithm is limited. In the proposed method, we detect a define boundary of cut using cut-detection algorithm. Then we adaptively apply a single-frame based super-resolution method to detected cut. Additionally, we propose algorithms of normalizing motion vector and analyzing pattern of edge to solve various problems of existing super-resolution algorithms. The experimental results show that the proposed algorithm has better performance than other conventional interpolation methods.