• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1527-1530
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• 2003

Video is an important and challenge media and requires sophisticated indexing schemes for efficient retrieval from visual databases. Scene change detection is the first step for automatic indexing of video data. Recently, several scene change detection algorithms in the pixel and compressed domains have been reported in the literature. However, using pixel methods are computationally complex and are not very robust in detecting scene change detection. In this paper, we propose robust abrupt scene change detection using macroblock type and DC coefficient. Experimental results show that the proposed algorithm is robust for detection of most abrupt scene changes in the compressed domain.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.859-862
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• 1998

Many playback methods of MPEG-1 video were developed and are have beendeveloped now. But nomal playback method demands great time. In this paper we designed and implemented the scene transition playback method of the MPEG-1 video data. The previous studies of scene transition playback have used to the DC or edge information after decoding process of picture. In this paper, scene transition is detected by macroblock information from MPEG-1 compressed area, then decodes and playbacks the only scene transition picture. This MPEG-1 video player was implemented by decoding control. So it is possible to add special playback method to MPEG-1 video player. As the result, which is proposed in this paper the scene transition method can minimize to decoding calculation and decrease to playback time of the MPEG-1 video data.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.298-305
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• 2012

In this paper, we propose an integrated algorithm for scene recognition, which has been a challenging computer vision problem, with application to mobile robot localization. The proposed scene recognition method utilizes SIFT and visual words as local-level features and GIST as a global-level feature. As local-level and global-level features complement each other, it results in improved performance for scene recognition. This improved algorithm is of low computational complexity and robust to image distortions.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.61-63
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• 2005

Retreiving indoor scene reference image from database using visual information is important issue in Robot Navigation. Scene matching problem in navigation robot is not easy because input image that is taken in navigation process is affinly distorted. We represent probabilistic framework for the feature matching between features in input image and features in database reference images to guarantee robust scene matching efficiency. By reconstructing probabilistic scene matching framework we get a higher precision than the existing feaure-feature matching scheme. To construct probabilistic framework we represent each image as Gaussian Mixture Model using Expectation Maximization algorithm using SIFT(Scale Invariant Feature Transform).

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.629-637
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• 2000

The content-based information retrieval for a multimedia database uses feature information extracted from the compressed videos. This paper presents an effective method to detect scene changes from compressed videos. Scene changes are detected with DC values of DCT coefficients in MPEG-1 encoded video sequences. Instead of decoding full frames. partial macroblocks of each frame, horizontal and vertical macroblocks, are decoded to detect scene changes. This method detects abrupt scene changes by decoding minimal number of blocks and saves a lot of computation time. The performance of the proposed algorithm is analyzed based on the precision and the recall. The experimental results show the effectiveness in computation time and detection rate to detect scene changes of various MPEG-1 video streams.

• The Journal of Information Systems
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• v.14 no.3
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• pp.117-122
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• 2005

This paper presents a method for detecting scene changes in video sequences, in which the $chi^{2}$-test is modified by imposing weights according to NTSC standard. To automatically determine threshold values for scene change detection, the proposed method utilizes the frame differences that are obtained by the weighted $chi^{2}$-test. In the first step, the mean and the standard deviation of the difference values are calculated, and then, we subtract the mean difference value from each difference value. In the next step, the same process is performed on the remained difference values, mean-subtracted frame differences, until the stopping criterion is satisfied. Finally, the threshold value for scene change detection is determined by the proposed automatic threshold estimation algorithm. The proposed method is tested on various video sources and, in the experimental results, it is shown that the proposed method is reliably estimates the thresholds and detects scene changes.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.101-105
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• 2020

In this study, we are going to discuss the role of sound, which exists as the background of a movie scene, and the relationship between seeing and hearing. In order to analyze the form in which the scene and sound are matched, the visual content of the image must be analyzed first. In this study, we analyzed Stanley Kubrick's film . Generally, there are both visual and auditory features in the scene of the movie. In some cases, the sound is emphasized more than the scene, and the scene is emphasized more than the sound. In particular, the sound in movies enables a wider imagination and a three-dimensional experience. Images and sounds will have different meanings and effects depending on the purpose of use. By analyzing the correlation between visual scene and auditory sound based on the role sound plays in the film in this study, we would like to confirm that sound is one essential element that has the role of equivalent and independent expression, not the role of assisting images.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.329-336
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• 2023

This paper introduces an edge AI-based scene-specific object detection system for long-term traffic management, focusing on analyzing congestion and movement via cameras. It aims to balance fast processing and accuracy in traffic flow data analysis using edge computing. We adapt the YOLOv5 model, with four heads, to a scene-specific model that utilizes the fixed camera's scene-specific properties. This model selectively detects objects based on scale by blocking nodes, ensuring only objects of certain sizes are identified. A decision module then selects the most suitable object detector for each scene, enhancing inference speed without significant accuracy loss, as demonstrated in our experiments.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.617-630
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• 2005

General scene change detection determines the changes of a scene by using feature comparison of two continuous images that are above the fixed threshold. But existing algerian detects scene change that was used in comparing the features of two images continuously, it usually takes a lot of time in decrypting the image data and false-detection problem occurs when there is an object motion or a change of illumination. In this paper, macroblock were used to extract the information directly from the MPEG compression area and suggests algorithm that will detect scene changes more effectively. Existing algorithm have shown numerous arithmetic problems that were improved in the proposed algorithm. The existing algorithm cannot detect the changes of a scene after analyzing the relationship of the previousand futureimages while the algorithm being proposed can detect the changes of a scene continuously and resolves the problem of false-detection. To this end, the data used in general were tested to prove that this algerian would be able to detect the scene changes faster and more correctly than the existing ones. The performance of the suggested algorithm was analyzed basedontheresultsoftheexperiment. .

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.74-89
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• 2021

For higher-level requirements of urban planning and management and the recent development of "digital earth" and "digital city", it is urgent to establish protocols for the construction of three-dimensional digital city models. However, some problems still exist in the digital technology of the three-dimensional city model, such as insufficient precision of the three-dimensional model, not optimizing the scene and not considering the constraints of building codes. In view of those points, a method to interactively simulate a virtual city scene based on building codes is proposed in this paper. Firstly, some constraint functions are set up to restrict the models to adhere to the building codes, and an improved directional bounding box technique is utilized to solve the problem that geometric objects may intersect in a virtual city scene. The three-dimensional model invocation strategy is designed to convert two-dimensional layouts to a three-dimensional urban scene. A Leap Motion hardware device is used to interactively place the 3D models in a virtual scene. Finally, the design and construction of the three-dimensional scene are completed by using Unity3D. The experiment shows that this method can simulate urban virtual scenes that strictly adhere to building codes in a virtual scene of the city environment, but also provide information and decision-making functions for urban planning and management.