• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.919-922
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• 1998

A content-base search method is required for video which has an unformatted and huge size of data. The index techniue 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 change a threshold value during the cut detection process. We demonstrate that the proposed method is more efficient than the existing methods.

• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.440-453
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• 2019

This study was carried out to investigate the effect of watching a two-dimensional (2D) forest video and a virtual reality (VR) forest video on stress reduction in adults. Experiments were conducted in an artificial climate room, and 40 subjects participated. After inducing stress in the subjects, subjects watched a 2D gray video, 2D forest video, or VR forest video for 5 mins. The autonomic nervous system activity was evaluated continuously in terms of measured heart rate variability during the experiment. After each experiment, the subject's psychological state was evaluated using a questionnaire. The 2D forest video decreased the viewer's stress index, increased HF, and reduced heart rate compared with the 2D gray video. The VR forest video had a greater stress index reduction effect, LF/HF increase effect, and heart rate reduction effect than the 2D gray video. Psychological measurements showed that subjects felt more comfortable, natural, and calm when watching the 2D gray video, 2D forest video or VR forest video. We also found that the 2D forest video and VR forest video increased positive emotions and reduced negative emotions compared to the 2D gray video. Based on these results, it can be concluded that watching the 2D forest and VR forest videos reduces the stress index and heart rate compared with watching the 2D gray video. Thus, it is considered that the 2D forest video increases the activity of the parasympathetic nervous system, and the VR forest video increases the activity of the sympathetic nervous system. The increased activity of the sympathetic nervous system upon watching the VR forest video is judged to be positive sympathetic nerve activity, such as novelty and curiosity, and not negative sympathetic activity, such as stress and tension. The results of this study are expected to be the basis for examining the visual effects of forest healing, with hope that the utilization of VR, the technology of the fourth industrial revolution in the forestry field, will broaden.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1130-1139
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• 1998

This paper presents an integrated solution for the content-based news video indexing and the retrieval. Currently, it is impossible to automatically index a general video, but we can index a specific structural video such as news videos. Our proposed model extracts automatically the key frames by using the structured knowledge of news and consists of the news item segmentation, caption recognition and search browser modules. We present above three modules in the following: the news event segmentation module recognizes an anchor-person shot based on face recognition, and then its news event are divided by the anchor-person's frame information. The caption recognition module detects the caption-frames with the caption characteristics, extracts their character region by the using split-merge method, and then recognizes characters with OCR software. Finally, the search browser module could make a various of searching mechanism possible.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1236-1247
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• 2017

In this paper, we propose a method for evaluating the uncomfortable shaking in the video. When you shoot a video using a handheld device, such as a smartphone, most of the video contains unwanted shake. Most of these fluctuations are caused by hand tremors that occurred during shooting, and many methods for correcting them automatically have been proposed. It is necessary to evaluate the shake correction performance in order to compare the proposed shake correction methods. However, since there is no standardized performance evaluation method, a correction performance evaluation method is proposed for each shake correction method. Therefore, it is difficult to make objective comparison of shake correction method. In this paper, we propose a method for objectively evaluating video shake. Automatically analyze the video to find out how much tremors are included in the video and how much the tremors are concentrated at a specific time. In order to measure the shaking index, we proposed jitter modeling. We applied the algorithm implemented by Optical Flow to the real video to automatically measure shaking frequency. Finally, we analyzed how the shaking indices appeared after applying three different image stabilization methods to nine sample videos.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1570-1578
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• 2000

Object motion is an important feature of content in video sequences. By now, various methods to exact feature about the object motion have been reported[1,2]. However they are not suitable to index video using the motion, since a lot of bits and complex indexing parameters are needed for the indexing [3,4] In this paper, we propose object motion map which could provide efficient indexing method for object motion. The proposed object motion map has both global and local motion information during an object is moving. Furthermore, it requires small bit of memory for the indexing. to evaluate performance of proposed indexing technique, experiments are performed with video database consisting of MPEG-1 video sequence in MPEG-7 test set.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.107-116
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• 1998

Video data are retrieved and stored in various compressed forms according to their characteristics. In this paper, we present a generic data model that captures the structure of a video document and that provides a means for indexing a video stream. Using this model, we design and implement CVIMS (the MPEG-2 Compressed Video Information Management System) to store and retrieve video documents. CVIMS extracts I-frames from MPEG-2 TS files, selects key-frames from the I-frames, and stores in database the index information such as thumbnails, captions, and picture descriptors of the key-frames. And, CVIMS retrieves MPEG-2 video data using the thumbnails of key-frames and various labels of queries. And also, the system is accessible by a web interface.

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1431-1440
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• 1998

Video data are retrieved and stored in various compressed forms according to their characteristics, In this paper, we present a generic data model that captures the structure of a video document and that provides a means for indexing a video stream, Using this model, we design and implement CVIMS (the MPEG-2 Compressed Video Information Management System) to store and retrieve video documents, CVIMS extracts I-frames from MPEG-2 files, selects key-frames from the I -frames, and stores in database the index information such as thumbnails, captions, and picture descriptors of the key-frames, And also, CVIMS retrieves MPEG- 2 video data using the thumbnails of key-frames and v31ious labels of queries.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1399-1404
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• 2004

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 an 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 rotor intelligence value, classified into diagonal direction. Pixel value of color detected in each frame of video data is stored as A(i, i) matrix - i is the number of frames, i is an image height of frame. By using the stored pixel value as the method of UE(Mean Square Error) 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 an experiment on the cut detection of lames comprehensively, 1 experimented on many kinds of video, analyzing and comparing efficiency of the cut detection system.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.69-82
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• 2004

A moving object has a special feature that it's spatial location, shape and size are changed as time goes. These changes of the object accompany the continuous movement that is called the trajectory. In this paper, we propose an index structure that users can retrieve the trajectory of a moving object with the access of a page. We also propose the multi-complex query that is a new query type for trajectory retrieval. In order to prove the excellence of our method, we compare and analyze the performance for query time and storage space through experiments in various environments. It is shown that our method outperforms the existing index structures when processing spatio-temporal trajectory queries on moving objects.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.294-300
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• 2004

According to the development of digital media technologies various algorithms for video clip matching have been proposed to match the video sequences efficiently. A large number of video search methods have focused on frame-wise query, whereas a relatively few algorithms have been presented for video clip matching or video shot matching. In this paper, we propose an efficient algorithm to index the video sequences and to retrieve the sequences for video clip query. To improve the accuracy and performance of video sequence matching, we employ the Cauchy function as a similarity measure between histograms of consecutive frames, which yields a high performance compared with conventional measures. The key frames extracted from segmented video shots can be used not only for video shot clustering but also for video sequence matching or browsing, where the key frame is defined by the frame that is significantly different from the previous frames. Experimental results with color video sequences show that the proposed method yields the high matching performance and accuracy with a low computational load compared with conventional algorithms.