• Korean Journal of Cognitive Science
• /
• v.11 no.2
• /
• pp.79-87
• /
• 2000

In this paper we present a face recognition and face detection algorithm in MPEG compressed video. The proposed method consists three stage of processing steps. The first step is to produce a spatially reduced DC image form MPEG compressed video for processing. And the second step is face detection on reduced DC image. Finally, the last step is face recognition on partially extracted compressed frames which contain the detected faces. The spatially reduced DC image is produced from two dimensional inverse DCT of the DC coefficient and the first two AC coefficients. The face detection is performed on DC image and face recognition is performed on one extracted frame per GOP by using the K-L transform. In order to evaluate the proposed method, we carried out experiments on video database. The experiment results show the proposed method is very efficient and helpful for target tasks.

• Proceedings of the KSME Conference
• /
• 2000.04b
• /
• pp.655-660
• /
• 2000

Animation technique from the PIV database is particularly emphasized to give macroscopic and quantitative description of complex flow fields. This paper shows animation construction and application example for the post-processing of PIV data. As examples, first case is a pitching airfoil immersed in tree surface water circulating tunnel. Second case is a wake of a model-ship. Third case of PIV data is a large scale surface flow field. Obtained images are processed in time sequence by PIV exclusive routines where an efficient and reliable cross correlation algorithm is included for vector identification. All. animation Jobs are implemented completely on single personal computer environment. Compressed digital images are obtained initially by Motion-JPEG board and various An files are finally obtained through graphic processes.

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

• KIISE Transactions on Computing Practices
• /
• v.23 no.4
• /
• pp.250-255
• /
• 2017

Given the explosion of genomic data and expansion of applications such as precision medicine, the importance of efficient genome-database management continues to grow. Traditional compression techniques may be effective in reducing the size of a database, but a new challenge follows in terms of performing operations such as comparison and searches on the compressed database. Based on that many genome databases typically have numerous duplicated or similar sequences, and that the runtime of genome analyses is normally proportional to the number of sequences in a database, we propose a technique that can compress a genome database by eliminating similar entries from the database. Through our experiments, we show that we can remove approximately 84% of sequences with 1% similarity threshold, accelerating the downstream classification tasks by approximately 10 times. We also confirm that our compression method does not significantly affect the accuracy of taxonomy diversity assessments or classification.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1124-1124
• /
• 2001

CARNAC is a procedure for obtaining quantitative analysis of a sample by comparison of the NIR spectra of the unknown sample with a database of a large number of samples with NIR spectral and compositional data. The method depends on the compression of the NIR database followed by a modification of the compressed data which emphasizes the required analyte. The method identifies a few very similar samples and the value of the required analyte is calculated from a weighed average of the analyte values for the selected similar samples. The method was originally described at Chambersburg IDRC in 1986 and in the Proceedings of the FT Conference of 1987. This contribution will describe recent work on utilising new methods for both compression and modification.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.9B
• /
• pp.1713-1720
• /
• 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 KIISE:Databases
• /
• v.37 no.3
• /
• pp.146-164
• /
• 2010

Due to an increasing volume of XML data, it is considered prudent to store XML data on an industry-strength database system instead of relying on a domain specific application or a file system. For shredded XML data stored in relational tables, however, it may not be straightforward to apply existing algorithms for twig query processing, since most of the algorithms require XML data to be accessed in a form of streams of elements grouped by their tags and sorted in a particular order. In order to support XML query processing within the common framework of relational database systems, we first propose several bitmap indexes and their strategies for supporting holistic twig joining on XML data stored in relational tables. Since bitmap indexes are well supported in most of the commercial and open-source database systems, the proposed bitmapped indexes and twig query processing strategies can be incorporated into relational query processing framework with more ease. The proposed query processing strategies are efficient in terms of both time and space, because the compressed bitmap indexes stay compressed during data access. In addition, we propose a hybrid index which computes twig query solutions with only bit-vectors, without accessing labeled XML elements stored in the relational tables.

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

• Journal of Korea Multimedia Society
• /
• v.14 no.7
• /
• pp.858-865
• /
• 2011

In order to allow the user to efficiently browse, select, and retrieve a desired video part without having to deal directly with GBytes of compressed data, classification of shot motion characteristic has to be carried out as a preparation for such user interaction. The organization of video information for video database requires segmentation of a video into its constituent shots and their subsequent characterization in terms of content and camera movement in shot. In order to classify shot motion, it is a conventional way to use element of motion vector. However, there is a limit to estimate global camera motion because the way that uses motion vectors only represents local movement. For shot classification in terms of motion information, we propose a new scheme consisting of partial decoding of INTRA pictures and comparing the x, y displacement vector curve between the decoded I-frame and next P-frame in compressed video data.

• The KIPS Transactions:PartD
• /
• v.15D no.6
• /
• pp.733-740
• /
• 2008

Recently, mobile computing devices are used popularly. And quantity of information on mobile computing devices is being increased due to digitalization of information. So it needs an embedded DBMS for effective information management. Furthermore, since flash memory having a restriction on the number of partial write cycles is rapidly deployed on mobile computing devices as data storage and is more expensive than the conventional magnetic hard disk, the compressed data management system(CDMS) has been considered as an effective storage management technique for mobile computing devices in previous research. However, the research of CDMS is at the initial stage and has several problems. Hence, in this paper, we present additional storage management methods to solve the problems and improve the effectiveness of the CDMS for embedded DBMS.