• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.169-188
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• 2009

The study proposed the algorithm for automatically summarizing the audio information from a video and then conducted an experiment for the evaluation of the audio extraction that was constructed based on the proposed algorithm. The research results showed that first, the recall and precision rates of the proposed method for audio summarization were higher than those of the mechanical method by which audio extraction was constructed based on the sentence location. Second, the proposed method outperformed the mechanical method in summary making tasks, although in the gist recognition task(multiple choice), there is no statistically difference between the proposed and mechanical methods. In addition, the study conducted the participants' satisfaction survey regarding the use of audio extraction for video browsing and also discussed the practical implications of the proposed method in Internet and digital library environments.

• The KIPS Transactions:PartB
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• v.11B no.5
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• pp.587-596
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• 2004

During recent years, a new framework, which aims to bring a unified and global approach in indexing, browsing and querying various digital multimedia data such as audio, video and image has been developed. This new system partitions each media stream into smaller units based on actual physical events. These physical events within oath media stream can then be effectively indexed for retrieval. In this paper, we present a new approach that exploits audio, image and video features to segment and analyze the audio-visual data. Integration of audio and visual analysis can overcome the weakness of previous approach that was based on the image or video analysis only. We Implement a web-based multi media data retrieval system called XCRAB and report on its experiment result.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.541-548
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• 2002

This paper proposes an XML based Multimedia Annotation and Retrieval System, which can represent and retrieve video data efficiently using XML. The system provides a graphical user interface for annotating, searching, and browsing multimedia data. It is Implemented based on the hierarchical metadata model to represent multimedia information. The metadata about video is organized based on multimedia description schema using XML Schema that basically conforms to the MPEG-7 standard. Also, for the effective indexing and retrieval of multimedia data, video segments are annotated and categorized using the closed caption.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.92-97
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• 1998

For the efficient searching and browsing of digital video, it is essential to extract the internal structure of the video contents. As an example, a news video consists of several sections such as politics, economics, sports and others, and also each section consists of individual topics. With this information in hand, users can ore easily access the required video frames. This paper addresses the problem of automatic shot boundary detection and selection of representative frames (R-frames), which are the essential step in recognizing the internal structure of video contents. In the shot boundary detection, a new algorithm that have dual detectors which are designed specifically for the abrupt boundaries (cuts) and gradually changing bounaries respectively is proposed. Compared to the existing 미algorithms that mostly have tried to detect both types by a single mechanism, the proposed algorithm is proved to be more robust and accurate. Also in the problem of R-frame selection, simple mechanical approaches such as selecting one frame every other second have been adopted. However this approach often selects too many R-frames in static short, while drops important frames in dynamic shots. To improve the selection mechanism, a new R-frame selection algorithm that uses motion information extracted from pixel difference is proposed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1713-1720
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• 1999

This paper presents a new key frame extraction technique, for scene change detection, using the proposed AHIM (Accumulative Histogram Intersection Measure) from the DC image constructed by DCT DC coefficients in the compressed video sequence that is video compression standard such as MPEG. For fast content-based browsing and video retrieval in a video database, we also provide a novel coarse-to-fine video indexing scheme. In the extracted key frame, we perform the region segmentation as a preprocessing. First, the segmented image is projected with the horizontal direction, then we transform the result into a histogram, which is saved as a database index. In the second step, we calculate the moments and change them into a distance value. From the simulation results, the proposed method clearly shows the validity and superiority in respect of computation time and memory space, and that in conjunction with other techniques for indexing, such as color, can provide a powerful framework for image indexing and retrieval.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.45-52
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• 2004

According tothe development of digital media technologies various algorithms for video sequence matching have been proposed to match the video sequences efficiently. A large number of video sequence matching methods have focused on frame-wise query, whereas a relatively few algorithms have been presented for video sequence matching or video shot matching. In this paper, we propose an efficientalgorithm to index the video sequences and to retrieve the sequences for video sequence 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 fames. Several key frame extraction algorithms have been proposed, in which similar methods used for shot boundary detection were employed with proper similarity measures. In this paper, we propose the efficient algorithm to extract key frames using the cumulative Cauchy function measure and. compare its performance with that of conventional algorithms. Video sequence matching can be performed by evaluating the similarity between data sets of key frames. To improve the matching efficiency with the set of extracted key frames we employ the Cauchy function and the modified Hausdorff distance. Experimental results with several color video sequences show that the proposed method yields the high matching performance and accuracy with a low computational load compared with conventional algorithms.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.529-542
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• 2000

Recent years, the use of multimedia information is rapidly increasing, and the video media is the most rising one than any others, and this field Integrates all the media into a single data stream. Though the availability of digital video is raised largely, it is very difficult for users to make the effective video access, due to its length and unstructured video format. Thus, the minimal interaction of users and the explicit definition of video structure is a key requirement in the lately developing image and video management systems. This paper defines the terms and hierarchical video structure, and presents the system, which construct the clustering-based video hierarchy, which facilitate users by browsing the summary and do a random access to the video content. Instead of using a single feature and domain-specific thresholds, we use multiple features that have complementary relationship for each other and clustering-based methods that use normalization so as to interact with users minimally. The stage of shot boundary detection extracts multiple features, performs the adaptive filtering process for each features to enhance the performance by eliminating the false factors, and does k-means clustering with two classes. The shot list of a result after the proposed procedure is represented as the video hierarchy by the intelligent unsupervised clustering technique. We experimented the static and the dynamic movie videos that represent characteristics of various video types. In the result of shot boundary detection, we had almost more than 95% good performance, and had also rood result in the video hierarchy.

• Journal of KIISE:Information Networking
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• v.30 no.4
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• pp.504-512
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• 2003

In this paper, we propose a new adaptive dissolve detection method based on the analysis of a dissolve modeling error which is the difference between an ideally modeled dissolve curve with no correlation and an actual dissolve curve including a correlation. The proposed dissolve detection method consists of two steps. First, candidate dissolve regions are extracted using the characteristics of a downward convex parabola, then each candidate region is verified based oil the dissolve modeling error. If the dissolve modeling error for a candidate region is less than a threshold defined by the target modeling error with a target correlation, the candidate region is determined as a resolve region with a lower correlation than the target correlation. The threshold is adaptively determined based on the variances between the candidate regions and the target correlation. By considering the correlation between neighbor scenes, the proposed method is able to be a semantic scene-change detector. The proposed method was tested on various types of data and its performance proved to be more accurate and reliable regardless of variation of variance of test sequences when compared with other commonly use methods.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.441-446
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• 2009

This paper proposes an automatic indexing algorithm of golf video using audio information. In the proposed algorithm, the input audio stream is demultiplexed into the stream of video and audio. By means of Adaboost-cascade classifier, the continuous audio stream is classified into announcer's speech segment recorded in studio, music segment accompanied with players' names on TV screen, reaction segment of audience according to the play, reporter's speech segment with field background, filed noise segment like wind or waves. And golf swing sound including drive shot, iron shot, and putting shot is detected by the method of impulse onset detection and modulation spectrum verification. The detected swing and applause are used effectively to index action or highlight unit. Compared with video based semantic analysis, main advantage of the proposed system is its small computation requirement so that it facilitates to apply the technology to embedded consumer electronic devices for fast browsing.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.338-345
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• 2011

Nowadays mobile devices are used for various applications such as making voice/video calls, browsing the Internet, listening to music etc. The average battery consumption of each of these activities and the length of time a user spends on each one determines the battery lifetime of a mobile device. Previous methods have provided predictions of battery lifetime using a static battery consumption rate that does not consider user characteristics. This paper proposes an approach to predict a mobile device's available battery lifetime based on usage patterns. Because every user has a different pattern of voice calls, data communication, and video call usage, we can use such usage patterns for personalized prediction of battery lifetime. Firstly, we define one or more states that affect battery consumption. Then, we record time-series log data related to battery consumption and the use time of each state. We calculate the average battery consumption rate for each state and determine the usage pattern based on the time-series data. Finally, we predict the available battery time based on the average battery consumption rate for each state and the usage pattern. We also present the experimental trials used to validate our approach in the real world.