• JSTS:Journal of Semiconductor Technology and Science
• /
• v.13 no.5
• /
• pp.430-442
• /
• 2013

This paper presents a fast multi-reference frame integer motion estimator for H.264/AVC. The proposed system uses the previously proposed fast multi-reference frame algorithm. The previously proposed algorithm executes a full search area motion estimation in reference frames 0 and 1. After that, the search areas of motion estimation in reference frames 2, 3 and 4 are minimized by a linear relationship between the motion vector and the distances from the current frame to the reference frames. For hardware implementation, the modified algorithm optimizes the search area, reduces the overlapping search area and modifies a division equation. Because the search area is reduced, the amount of computation is reduced by 58.7%. In experimental results, the modified algorithm shows an increase of bit-rate in 0.36% when compared with the five reference frame standard. The pipeline structure and the memory controller are also adopted for real-time video encoding. The proposed system is implemented using 0.13 um CMOS technology, and the gate count is 1089K with 6.50 KB of internal SRAM. It can encode a Full HD video ($1920{\times}1080P@30Hz$) in real-time at a 135 MHz clock speed with 5 reference frames.

• The KIPS Transactions:PartC
• /
• v.9C no.1
• /
• pp.9-16
• /
• 2002

As existing analog video surveillance systems could save and retrieve data only in a limited space within short distance, it had many constraints in developing into various application systems. However, on the back of development of the Internet and computer technologies, digital video surveillance systems can be controlled from a remote location by web browser without space limits. Moreover, data compression and management technologies with Index Search algorithm make it possible to efficiently handling, storing, and retrieving a large amount of data and further motion detection algorithm enhances a recording speed and efficiency for a practical application, that is, a practical remote recordable video surveillance system using our efficient algorithms as mentioned, called WebCam. The WebCam server system can intelligently record and save video images digitized through efficient database management, monitor and control cameras in a remote place through user authentication, and search logs.

• Journal of Korea Multimedia Society
• /
• v.4 no.3
• /
• pp.205-214
• /
• 2001

As the real time multimedia data service has become available due to the rapid progress of computer and Internet technology, the users can enjoy the newly developed service, which is called Video On-Dem-and(VOD). However, most of service providers have not paid their attention much on the software for various service modes on VOD, but they are only concentrating un the hardware to provide with the high resolution video display. Therefore, the service providers are recently to pay more attention on the software to cope with the various demands of users than hardware. So this paper has designed and implemented the VOD service system for those demands. Since the VOD service system suggested by this paper enable off-line search functions through E-mail, the users can possibly get the necessary information from off-line Search without connecting to the server while the current VOD service can prominently help users to save the time and effort to sea고 and select the Video contents by using periodical current awareness service supported by PUSH technology and user oriented information booking and feedback service supported by SDI service.

• The KIPS Transactions:PartB
• /
• v.10B no.6
• /
• pp.687-694
• /
• 2003

According to the rapid increase of multimedia data quantity recently, various means of video data search has been desired. In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we design the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.22 no.7
• /
• pp.37-42
• /
• 2008

In this paper, a real-time multiview video coding system using fast disparity estimation is proposed. In the multiview encoder, adaptive disparity-motion estimation (DME) for an effective 3-dimensional (3D) processing are proposed. That is, by adaptively predicting the mutual correlation between stereo images in the key-frame using the proposed algorithm, the bandwidth of stereo input images can be compressed to the level of a conventional 2D image and a predicted image also can be effectively reconstructed using a reference image and adaptive disparity vectors. Also, in multiview decoder, intermediate view reconstruction (IVR) using adaptive disparity search algorithm (DSA) for real-time multiview video processing is proposed. The proposed IVR can reduce a processing time of disparity estimation by selecting adaptively disparity search range. Accordingly, the proposed multiview video coding system is able to increase the efficiency of the coding rate and improve the resolution.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
• /
• v.10 no.3
• /
• pp.103-109
• /
• 2011

With the growing popularity of digital video applications, those areas of the efficient transmit, storage management, and search technology for video data are emerging as an important core technology. To be an effective video indexing system, users need to be able to find the video segments that they want. Unfortunately, video data is difficult to manage because of its unstructured data type and large volume with linear forms. This paper proposes a shot verification using visual rhythm and video retrieval system. The shot verification is designed to detect a segment from video easily and quickly, known as shot boundaries, just by changing the visual rhythm without playing the image. Therefore, this can decrease the false detected shots and generate the unidentified shots and key frames. The retrieval system is constructed in terms of visual descriptor from the list of MPEG-7. The effectiveness of the proposed shot verification process and video retrieval system is demonstrated.

• Journal of Broadcast Engineering
• /
• v.7 no.2
• /
• pp.114-125
• /
• 2002

Although there have been a lot of researches on a video abstraction algorithm, the video abstraction tool is necessary to correctly pick up some important shots in a video because the important shots might vary on the person's subjectivity. This paper proposes a video abstraction and search system for making a video abstraction automatically or manually. Proposed system has two main components, server and client. The server generates the Metadata and makes a video abstraction file. The description for video abstraction file is based on MPEG-7. Since proposed system has a function to manually correct the results of each step, the author could produce a good video abstraction easily and efficiently. The proposed system could be used to build a digital video library.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.2
• /
• pp.29-35
• /
• 2023

This paper makes it possible to search videos based on sentence by improving the previous research which automatically generates rich metadata from videos and searches videos by key words. For search by sentence, morphemes are analyzed for each sentence, keywords are extracted, weights are assigned to each keyword, and some videos are recommended by applying a ranking algorithm developed in the previous research. In order to evaluate performance of video search in this paper, a sufficient amount of videos and sufficient number of user experiences are re required. However, in the current situation where these are insufficient, three indirect evaluation methods were used: evaluation of overall user satisfaction, comparison of recommendation scores and user satisfaction, and evaluation of user satisfaction by video categories. As a result of performance evaluation, it was shown that the rich metadata construction and video recommendation implementation in this paper give users high search satisfaction.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.6
• /
• pp.85-91
• /
• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.4
• /
• pp.95-102
• /
• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency md requires many efforts of system administrator or annotator because of imperfect automatic processing. In this paper, we propose semantics-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method and optimized comparison area extracting that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantics-based retrieval.