• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.37-43
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• 2016

This paper introduces a method for video shot group detection needed for efficient management and summary of video. The proposed method detects shots based on low-level visual properties and performs temporal and spatial clustering based on visual similarity of neighboring shots. Shot groups created from temporal clustering are further clustered into small groups with respect to visual similarity. A set of representative shot frames are selected from each cluster of the smaller groups representing a scene. Shots excluded from temporal clustering are also clustered into groups from which representative shot frames are selected. A number of video clips are collected and applied to the method for accuracy of shot group detection. We achieved 91% of accuracy of the method for shot group detection. The number of representative shot frames is reduced to 1/3 of the total shot frames. The experiment also shows the inverse relationship between accuracy and compression rate.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.229-232
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• 2009

Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see real-time operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST Company. Thus, our algorithm in the paper can be useful in PMP or other portable players.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.49-56
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• 2012

In this paper, we propose the method that decides the shot types using face detection technique. The shot types, such as close-up shot, medium shot, and long shot, can be applied as useful information for understanding narrative structure of movies. The narrative structure of movie is builded by characters. Also their mental and emotional changes become inextricably bound up with them of narrative. The shot types are decided by distance between character and camera. If put together above them, shot types can be found by using detection technique of face size of characters and understand narrative of movie. To do this, we propose the methodology to detect shot type by face detecting and implement the system to do it. Additionally, we evaluate the performance of the system. The implementation system has been evaluated as 95% for close-up shot detection and 90% for medium shot detection, while 53.3% is just detected for long shots.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.103-109
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• 2007

In this paper, we detect shot boundaries using $X^2$-histogram comparison method which have enough spatial information that is more robust to the camera or object motion and produce more precise results. Also, we present normalization method to change Log-Formula and constant that is used for contrast enhancement of image in image processing and apply in difference value. And, present shot boundary detection algorithm to detect shot boundary based on general shot and abrupt shot's characteristic.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.1
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• pp.50-59
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• 2007

In this paper, an anchor shot detection method, which is a basic technology for managing news videos for index and retrieval purposes is proposed. To do that, two most popular news program such as 'KBS 9 Hour News' and 'MBC 9 Hour News' are analyzed and 4-step rule based detection method is proposed First, in the preprocessing, video shot boundaries are detected and the 1st frame of each shot is extracted as a key frame. Then, the detected shot is declared as an anchor shot, if all the following 4 conditions are satisfied. 1) There is an anchor face in the key frame of a shot. 2) Spatial distribution of edges in the key frame is adequate. 3) Background color information of the key frame is similar to the color information of an anchor model. 4) Motion rate in the shot is low. In order to show the validity of the proposed method, three 'KBS 9 Hour News' and three 'MBC 9 Hour News', which have total running time of 108 in minute and are broadcasted at different days, are used for experiments. Average detection rates showed 0.97 in precision, 1.0 in recall, and 0.98 in F-measure.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.58-63
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• 2000

This paper describes an efficient algorithm for shot boundary detection in MPEG video stream. There are two types of shot boundary: abrupt and gradual. The proposed algorithm for detecting the abrupt shot boundaries used DCT DC value in compressed domain. The proposed algorithm of the gradual change detection consists of two-pass mechanism. In the first pass, the expected positions of shot boundaries are extracted using ratio value of motion vectors. After decoding frames that are extracted in the first pass, we will make the dissolving image using (n)th and (n+2)th image of expected position. The gradual shot boundaries are selected by similarity of the dissolving image and the image of (n+1)th expected position. As applying the algorithm for detecting shot boundaries, the gradual changes as well as the abrupt changes are detected efficiently. Experimental results indicate that the proposed method is computationally fast for detecting shot boundaries and robust to the variation of the video characteristic that is different for the kind of videos.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.145-148
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• 2007

The video shot detection based on video picture type is presented in this paper. The detection algorithm is used MPEG compressed video frame directly, not reconstructed the original image. For shot detection, I and P frame of MPEG video bit stream are classified. The detecting scene cuts at I pictures are detected by reconstructed DC image. While scene cuts at P picture frame by monitoring the percentage of Intra-macroblocks per P picture. Experimental results on the test video bit stream is shown the detection rate of $85\sim98%$ and searching time is 4 times faster than the previously known video shot detection algorithm on the decompressed video shot.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.133-138
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• 2008

In this paper, we propose a novel anchor shot detection system, named to MASD (Multi-phase Anchor Shot Detection), which is a core step of the preprocessing process for the news video analysis. The proposed system is composed of four modules and operates sequentially: 1) skin color detection module for reducing the candidate face regions; 2) face detection module for finding the key-frames with a facial data; 3) vector representation module for the key-frame images using a non-negative matrix factorization; 4) one class SVM module for determining the anchor shots using a support vector data description. Besides the qualitative analysis, our experiments validate that the proposed system shows not only the comparable accuracy to the recently developed methods, but also more faster detection rate than those of others.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.217-220
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• 2007

In this paper, we present a new anchor shot detection system which is a core step of the preprocessing process for the news video analysis. The proposed system is composed of four modules and operates sequentially: 1) skin color detection module for reducing the candidate face regions; 2) face detection module for finding the key-frames with a facial data; 3) vector representation module for the key-frame images using a non-negative matrix factorization; 4) anchor shot detection module using a support vector data description. According to our computer experiments, the proposed system shows not only the comparable accuracy to the recent other results, but also more faster detection rate than others.

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.269-272
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• 2007

The shortcut shot detection based on MPEG compressed video bitstream is presented in this paper. The detection algorithm is used the video picture frame from MPEG compressed video directly not to be decompressed the original image. For shortcut detection, I and P frame of MPEG video bitstream are classified. The changing scene cuts at I pictures are detected by the decompressed DC image and scene cuts at P picture frame by monitoring the percentage of intra-macroblocks per P picture are detected. Experimental results using test video bitstream QVGA results in average 92% detection rate, searching time is taken around 4.5 times faster in comparison with changing scene shot detection algorithm which is decompressed the compressed bitstream.